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Inferring bacterial cell size dynamics across media conditions
Abstract Under stable growth conditions, bacteria maintain cell size homeostasis through coordinated elongation and division. Changes in nutrient availability perturb these mechanisms, resulting in dynamic regulation of the target cell size. Using microscopy imaging and mathematical modeling, we studied how bacterial cell volume changes over the population growth curve and found that Escherichia coli and Salmonella enterica , in stationary phase, exhibit similar cell volume distributions irrespective of growth media. Resuspending cells in rich media resulted in a transient increase in cell volume to a media-dependent maximum cell volume after $$\approx$$ 2h before decreasing to the stationary phase cell size. Interestingly, stabilizing the growth phase through continuous fresh media supply sustained the size distribution. In poor media conditions, cell volume changed minimally over the growth curve, but cell width was markedly decreased. This cell volume dynamics along the growth curve can be related to a similar increase and decrease dynamics of the ratio between cell density ( $$\text{OD}_{600}$$ ) and cell numbers (CFU). We developed a simple mathematical modeling framework that predicted a time-varying division rate needed to capture the dynamics of the mean cell size across media conditions. The proposed analysis can be used for comparison of cell size regulation mechanisms across dynamic environments when single-cell tracking is not possible.
Disease tolerance and infection pathogenesis age-related tradeoffs in mice
Abstract Disease tolerance is a defence strategy essential for survival of infections, limiting physiological damage without killing the pathogen 1,2 . The disease course and pathology an infection may cause can change over the lifespan of a host due to the structural and functional physiological changes that accumulate with age. Because successful disease tolerance responses require the host to engage mechanisms that are compatible with the disease course and pathology caused by an infection, we predicted that this defence strategy would change with age. Animals infected with a 50% lethal dose (LD 50 ) of a pathogen often show distinct health and sickness trajectories due to differences in disease tolerance 1,3 and can be used to define tolerance mechanisms. Here, using a polymicrobial sepsis model, we found that, despite having the same LD 50 , aged and young susceptible mice showed distinct disease courses. In young survivors, cardiac Foxo1 and its downstream effector Trim63 (MuRF1) protected from sepsis-induced cardiac remodelling, multi-organ injury and mortality. Conversely, in aged hosts, Foxo1 and Trim63 acted as drivers of sepsis pathogenesis and death. Our findings have implications for the tailoring of therapy to the age of an infected individual and indicate that disease tolerance genes show antagonistic pleiotropy.
HIF sustain a transcriptional regulatory circuit of EPAS1 expression in renal clear cell carcinoma
Abstract Initiation and sustainment of oncogenic signaling is a hallmark of cancer evolution and progression. In renal clear cell carcinoma, loss of von Hippel-Lindau protein causes stabilization of hypoxia-inducible transcription factors (HIF) evoking a pseudo-hypoxic response, perturbing epithelial homeostasis and leading to cancer development. Although genetic polymorphisms link the EPAS1 oncogene (coding for HIF-2α) to renal cancer and anti-HIF-2 compounds emerge as renal tumor therapies, little is known about transcriptional dysregulation of this factor in renal malignancies. We use genetic, epigenetic and transcriptomic data from large patient cohorts and cell models to dissect mechanisms of augmented EPAS1 transcription in clear cell renal cell carcinoma. We define an oncogenic enhancer of EPAS1 which operates depending on the presence of HIF and renal lineage-specific factors, thereby providing evidence for an auto-regulatory feed-forward circuit of HIF-2α regulation which promotes renal cancer growth.
Correction: 3D FusionNet for synthetic CT based lung cancer segmentation
From urban NPOs to rural knowledge networks: applying benefit-sharing models to African genomics research
Discovery of hydroxytriazole as a potential glyoxalase-I inhibitor utilizing computer-aided drug design techniques
Abstract The glyoxalase system, particularly Glyoxalase-I (Glo-I), plays a crucial role in detoxifying aldehyde metabolites into lactic acid. Inhibiting this enzyme causes the buildup of the poisonous aldehyde, leading to programmed cell death. In this study, molecular modelling techniques were employed, including high-throughput virtual screening (HTVS), followed by filtration procedures such as Lipinski’s rule of five and Veber’s rules, and finally CDOCKER docking, to prioritize compounds from the commercial Maybridge database. Sixteen compounds were carefully chosen and purchased from the Maybridge database for further experimental evaluation. The integrated computational and experimental workflow successfully culminated in the identification of a novel, potent Glyoxalase-I (Glo-I) inhibitor. One molecule has been discovered to inhibit Glo-I with an IC 50 of 11.1 µM . An analysis of the molecular dynamics of the active ligand ( SPB07393SC ) reveals stable behaviour. Crucially, this molecule incorporates a unique hydroxy triazole moiety, representing the first reported instance of this zinc-coordinating group in a Glo-I inhibitor. This will be utilized for the purpose of developing novel compounds with enhanced activity following appropriate modifications.
Composite SMG5-SMG6 PIN domain formation is essential for NMD
Abstract Nonsense-mediated mRNA decay (NMD) relies on the coordinated assembly and action of multiple protein factors. Degradation of target mRNAs begins with endonucleolytic cleavage near premature stop codons, but the mechanisms of endonuclease activation and regulation remain unclear. Using structural predictions, biochemical in vitro assays, and cell-based NMD analysis, we show that SMG5 and SMG6 interact via their PIN domains to form a composite interface (cPIN) with full endonuclease activity. In vitro reconstituted SMG5-SMG6 cPIN heterodimers show high activity, as SMG5 completes the SMG6 active site and substrate binding site. Mutations in residues at their predicted interaction surfaces, RNA-binding sites, or active site attenuate or abolish cPIN activity in vitro and impair cellular NMD. Our findings demonstrate how paralogous PIN domains complement each other to assemble a highly active endonuclease in NMD, providing a structural and mechanistic explanation for efficient NMD substrate degradation.
Cardiorespiratory fitness responses to a Daily Mile program in overweight youth from a low-income Colombian school
Abstract This study evaluated the effects of a 10-week Daily Mile (DM) intervention on physical fitness and plantar pressure in overweight and obese adolescents from a low-income school in Colombia. A parallel group experimental pilot study was conducted with adolescents aged 11–17 from a Colombian school. Participants were randomly assigned to an intervention group (IG, n = 21) that performed DM three days/week in addition to the usual curriculum, or to a control group (CG, n = 24). Outcomes included anthropometry, blood pressure, muscular fitness, baropodometry, and cardiorespiratory fitness (CRF). A hierarchical multiple linear regression was used to assess the intervention’s effect on CRF.No significant differences between groups were observed in anthropometry, blood pressure, muscular fitness, or baropodometry variables. In contrast, CRF significantly improved in the IG, with an average increase of ∼ 150 m in the Shuttle Run Test compared to controls (CG: 517.61 (71.93) vs. IG: 400.00 (182.29) m, p = 0.028). Hierarchical regression confirmed this effect (β = 149.88; CI 95% 55.8–210.0, p = 0.002). In this pilot study, a 10-week DM intervention resulted in short-term improvements in CRF among overweight and obese adolescents from a low-income Colombian school. These findings provide preliminary evidence of the feasibility of implementing DM within the school routine and support its potential to elicit favorable cardiorespiratory adaptations, warranting further investigation in larger and longer-term studies in this context.
Vulnerability of short-term memory in a mouse model of Alzheimer’s disease
Abstract Interference from distracting stimuli renders short-term memory vulnerable. While behavioral evidence suggests short-term memory deficits in Alzheimer’s disease (AD), the underlying neural mechanisms remain poorly understood. Using a mouse model of AD (APP-KI), we identified increased susceptibility of short-term memory to sensory perturbations. Simultaneous two-photon calcium imaging across eight cortical regions during a delayed-response task showed that distractors disrupted neural selectivity at both single-neuron and population levels in APP-KI mice. Recurrent neural network models replicating the neural activity of APP-KI mice exhibited decreased stability, consistent with reduced functional connectivity across the dorsal cortex. Furthermore, analyses of multi-regional corticocortical communication revealed reduced spatiotemporal degeneracy in activity transmission within the dorsal cortex of APP-KI mice, which could account for their attenuated robustness during sensorimotor transformations. Collectively, these findings identify reduced functional connectivity and impaired spatiotemporal degeneracy as central mechanisms of short-term memory deficits in the APP-KI mouse model of AD.
Seasonal and spatial shifts in the volatile chemical profile of Cymodocea nodosa across marine and lagoon ecosystems
A roadmap for evaluating moral competence in large language models
Emergent giant topological Hall effect in twisted Fe3GeTe2 metallic system
Quantum-secured routing in drone communication for 6G-enabled smart mobility
Iron-borane catalyzed carbonyl hydroboration and isolation of an iron(I)-ketyl radical
Abstract Hydroboration of carbonyl compounds has proven a pivotal route to access alcohols and other C1 moieties in recent years. Despite this, iron-based catalyst systems are somewhat limited with very little mechanistic understanding of these systems developed. Here we show that an iron metalloborane complex [{( i Pr DPB Ph )Fe} 2 (μ−1,2-N 2 )] ( A ) is an efficient pre-catalyst for hydroboration of ketones, cyclic esters and CO 2 with mild conditions. Mechanistic insights reveal a previously unreported direct iron(0)-mediated ligand-to-ligand hydride transfer (LLHT) process is in operation with B–H bond breaking being rate determining, indicating the importance of mechanistic studies on well-known transformations. An iron(I)-benzophenone ketyl radical with a unique S = 1 antiferromagnetic ground state has been isolated and fully characterized.
Breast imaging with ultra-low field MRI
Publisher Correction: A domed pachycephalosaur from the early Cretaceous of Mongolia
From single-sequences to evolutionary trajectories: protein language models capture the evolutionary potential of SARS-CoV-2
Abstract Protein language models (PLMs) capture features of protein three-dimensional structure from amino acid sequences alone, without requiring multiple sequence alignments (MSA). The concepts of grammar and semantics from natural language have been suggested to have the potential to capture functional properties of proteins. Here, we investigate how these representations enable assessment of variation due to mutation. Applied to the SARS-CoV-2 spike protein via in silico deep mutational scanning (DMS), the PLM ESM-2 captures evolutionary constraints directly from sequence context, recapitulating what normally requires MSA data. Unlike other state-of-the-art methods which require protein structures or multiple sequences for training, we show what can be accomplished using an unmodified pretrained PLM. Applied to SARS-CoV-2 variants across the pandemic, we demonstrate that ESM-2 representations encode the evolutionary history between variants, as well as the distinct nature of variants of concern upon their emergence, associated with shifts in receptor binding and antigenicity. ESM-2 likelihoods can also identify epistatic interactions among sites in the protein. Our results here affirm that PLMs like ESM-2 are broadly useful for variant-effect prediction, including unobserved changes, and can be applied to understand novel viral pathogens with the potential to be applied to any protein sequence, pathogen or otherwise.