bluuebunny/crossref_metadata_2025_split huggingface dataset:
Rho and a riboswitch regulatemntPexpression evading manganese stress and membrane toxicity
Authors: Prakash Anand , Kalita Arunima , Bhardwaj Kanika , Mishra Rajesh Kumar , Ghose Debarghya , Kaur Gursharan , Pani Bibhusita , Nudler Evgeny , Dutta Dipak 
Published: December 2023

AbstractThe trace metal ion manganese in excess is toxic. Therefore, a small subset of factors tightly maintains its cellular level, among which an efflux protein MntP is the champion. Multiple transcriptional regulators and a manganese-dependent translational riboswitch regulate the MntP expression. As riboswitches are untranslated RNAs, they are often associated with the Rho-dependent transcription termination in bacteria. Here we demonstrate that Rho efficiently terminates transcription at themntPriboswitch region. The addition of manganese activates the riboswitch, thereby restoring the coupling between transcription and translation to evade Rho-dependent transcription termination partially. Deletion of the riboswitch abolishes Rho-dependent termination and renders bacteria sensitive to manganese due to overexpression ofmntP. The highmntPexpression is associated with reactive oxygen species (ROS) production, slow growth, and cell filamentation phenotypes. We posit that manganese-dependent transcriptional activation in the absence of Rho-dependent termination leads to the observed toxicity arising from excessive MntP expression, a membrane protein. Thus, we identified a novel regulatory role of Rho in preventing membrane protein toxicity by terminating at the riboswitch element.
Gut Microbiome Dynamics and Predictive Value in Hospitalized COVID-19 Patients: A Comparative Analysis of Shallow and Deep Shotgun Sequencing
Authors: Kopera Katarzyna , Gromowski Tomasz , Wydmański Witold , Skonieczna-Żydecka Karolina , Muszyńska Agata , Zielińska Kinga , Wierzbicka-Woś Anna , Kaczmarczyk Mariusz , Kadaj-Lipka Roland , Cembrowska-Lech Danuta , Januszkiewicz Kornelia , Kotfis Katarzyna , Witkiewicz Wojciech , Nalewajska Magdalena , Feret Wiktoria , Marlicz Wojciech , Łoniewski Igor , Łabaj Paweł P. , Rydzewska Grażyna , Kosciolek Tomasz 
Published: December 2023

ABSTRACTThe COVID-19 pandemic caused by SARS-CoV-2 has led to a wide range of clinical presentations, with respiratory symptoms being common. However, emerging evidence suggests that the gastrointestinal (GI) tract is also affected, with angiotensin-converting enzyme 2, a key receptor for SARS-CoV-2, abundantly expressed in the ileum and colon. The virus has been detected in GI tissues and fecal samples, even in cases with negative respiratory results. GI symptoms have been associated with an increased risk of ICU admission and mortality. The gut microbiome, a complex ecosystem of around 40 trillion bacteria, plays a crucial role in immunological and metabolic pathways. Dysbiosis of the gut microbiota, characterized by a loss of beneficial microbes and decreased microbial diversity, has been observed in COVID-19 patients, potentially contributing to disease severity. We conducted a comprehensive gut microbiome study in 204 hospitalized COVID-19 patients using both shallow and deep shotgun sequencing methods. We aimed to track microbiota composition changes induced by hospitalization, link these alterations to clinical procedures (antibiotics administration) and outcomes (ICU referral, survival), and assess the predictive potential of the gut microbiome for COVID-19 prognosis. Shallow shotgun sequencing was evaluated as a cost-effective diagnostic alternative for clinical settings.
Imitating the ‘breeder’s eye’: predicting grain yield from measurements of non-yield traits
Authors: Jin Hongyu , Tross Michael C. , Tan Ruijuan , Newton Linsey , Mural Ravi V. , Yang Jinliang , Thompson Addie M. , Schnable James C. 
Published: December 2023

AbstractPlant breeding relies on information gathered from field trials to select promising new crop varieties for release to farmers and to develop genomic prediction models that can enhance the efficiency and rate of genetic improvement in future breeding cycles. However, field trials conducted in one environment provide limited insight into how well crop varieties will perform in other environments. As the pace of climate change intensifies, the time lag of developing and deploying new crop varieties indicates that plant breeders will need to make decisions about new crop varieties without knowing the future environments those crop varieties will encounter in farmers’ fields. Therefore, significant improvements in cross-environment prediction of crop performance are essential for creating and maintaining resilient agricultural systems in the latter half of the twenty-first century. To address this challenge, we conducted linked yield trials of 752 public maize genotypes in two distinct environments: Lincoln, Nebraska, and East Lansing, Michigan. Our findings confirmed that genomic predictions of yield can outperform direct yield measurements used to train the genomic prediction model in predicting yield in a second environment. Additionally, we developed and trained another trait-based yield prediction model, which we refer to as the Silicon Breeder’s Eye (SBE). Our results demonstrate that SBE prediction has comparable predictive power to genomic prediction models. SBE prediction has the potential to be applied to a wider range of breeding programs, including those that lack the resources to genotype large populations of individuals, such as programs in the developing world, breeding programs for specialty crops, and public sector programs.
Tradeoffs in the Design of RNA Thermometers
Authors: Gola Krishan Kumar , Patel Abhilash , Sen Shaunak 
Published: December 2023

AbstractThe synthesis of RNA thermometers is aimed at achieving temperature responses with desired thresholds and sensitivities. Although previous works have generated thermometers with a variety of thresholds and sensitivities as well as guidelines for design, possible constraints in the achievable thresholds and sensitivities remain unclear. We addressed this issue using a two-state model and its variants, as well as melt profiles generated from thermodynamic computations. In the two-state model, we found that the threshold was inversely proportional to the sensitivity, in the case of a fixed energy difference between the two states. Notably, this constraint could persist in variations of the two-state model with sequentially unfolding states and branched parallel pathways. Furthermore, the melt profiles generated from a library of thermometers exhibited a similar constraint. These results should inform the design of RNA thermometers as well as other responses that are mediated in a similar fashion.
Perivascular Excitation Tunnelling: a Novel and Preventable Cause of Cardiac Reperfusion Arrhythmias
Authors: Chleilat Enaam , Walz Teo Puig , Han Bo , Quinn T Alexander , Kohl Peter , Zgierski-Johnston Callum M 
Published: December 2023

AbstractBackgroundReperfusion after myocardial ischaemia can lead to deadly arrhythmias, in part due to heterogeneities in electrophysiology (EP) across affected tissue. There is a need to understand the spatiotemporal dynamics of ischaemia-reperfusion arrhythmias (IRA), so that reperfusion strategies to prevent them can be found.MethodsLangendorff-perfused rabbit isolated hearts were loaded with a voltage-sensitive dye. Epifluorescence imaging was used to track action potential propagation across the cardiac surface. The heart was simultaneously perfused ‘globally’ (viathe aorta) and ‘locally’ (viacannulation of a single coronary artery) with an oxygenated physiological saline solution. Local perfusion was subsequently switched to and from solutions that mimic aspects of ischaemia (acidosis, hypoxia, hyperkalaemia, or a simulated ischaemia solution combining all three) or to no-flow. Subsequently, different reperfusion strategies were tested to reduce IRA re-entries. The most successful strategy for preventing re-entry was tested in Langendorff-perfused isolated pig hearts to assess the clinical relevance of the observed mechanism and treatment strategy.ResultsUpon sudden reperfusion of the cannulated coronary artery in rabbit hearts we observed a preferential recovery of electrical excitability along the vessel’s main branch (‘perivascular excitation tunnelling’, PVET). This resulted in re-entry in roughly half of the hearts. Hyperkalaemia and hypoxia, but not acidosis, were sufficient to lead to conduction block, PVET, and re-entry, with both PVET and re-entry more frequently observed after hyperkalaemia than hypoxia.PVET was also present in pigs and PVET-based re-entries were successfully prevented in rabbit and pig hearts by two-step reperfusion, first of the distal majority of the previously ischaemic region, and then of the remaining tissue from the proximal point. With this strategy, any PVET that developed in the distal tissue was blocked by the still inexcitable proximal tissue. Upon reperfusion of the proximal tissue, there was a reduced path length for PVET. As a consequence, the associated excitable gap was too short for re-entrant excitation.ConclusionsWe observed a novel arrhythmia mechanism upon coronary reperfusion (PVET), which suggests that preferential recovery of myocardial excitability along the reperfused vessel is an important mechanism underlying IRA formation. PVET-induced re-entry reliably occurred in both rabbit and pig hearts and could be prevented by two-step reperfusion.Graphical Abstract
Investigation of astrocytes’ morphological changes in response to laser-induced shockwave
Authors: Pouladian Pegah , Ho Janelle , Perez Nicolas , Wakida Nicole M. , Gomez-Godinez Veronica , Preece Daryl 
Published: December 2023

AbstractTraumatic Brain Injury (TBI) arises from an external force affecting the brain, leading to a range of outcomes from mild to severe. Despite continuous scientific advancements, it continues to pose a persistent threat and remains a significant cause of physical impairment and mortality.Various models, including blast-induced TBI (bTBI), have been proposed to simulate TBI. Laser-induced shockwaves (LIS) us emerging as an effective method. LIS generates shockwaves via pulsed laser-induced plasma formation, offering a controlled means to study TBI at the cellular level. Astrocytes, pivotal in maintaining brain function post-injury, undergo dynamic morphological changes, contributing to the understanding of injury responses and neurodegenerative diseases.This study introduces a system combining Laser-Induced Shockwaves (LIS) and Quantitative Phase Microscopy (QPM) to quantify morphological changes in astrocytes during and after LIS exposure. QPM, a label-free method, facilitates 3D imaging and captures real-time cellular dynamics. The integration of LIS and QPM enables the assessment of astrocyte responses to shear stress caused by LIS, revealing immediate and sustained morphological transformations.Analysis post-LIS exposure indicates significant alterations in circularity, volume, surface area, and other features. Statistical tests affirm of observed trends, providing insights into astrocyte responses to mechanical forces. The findings contribute to understanding how mechanical stimuli impact astrocyte morphology, holding promise for targeted therapeutic strategies in traumatic brain injuries and related neurological disorders. The integrated LIS and QPM approach serves as a powerful tool for 3D imaging and quantitative measurement of astrocyte morphological changes, offering deeper insights into cellular dynamics and potential therapeutic interventions.
miRVim: Three-dimensional miRNA Structure Data Server
Authors: Sahu Vishal Kumar , Parida Ankita Subhadarsani , Ranjan Amit , Basu Soumya 
Published: December 2023

AbstractMicroRNAs (miRNAs), a distinct category of non-coding RNAs, exert multifaceted regulatory functions in a variety of organisms, including humans, animals, and plants. The inventory of identified miRNAs stands at approximately 60,000 among all species and 1,926 inHomo sapiensmanifests miRNA expression. Their theranostic role has been explored by researchers over the last few decades, positioning them as prominent therapeutic targets as our understanding of RNA targeting advances. However, the limited availability of experimentally determined miRNA structures has constrained drug discovery efforts relying on virtual screening or computational methods, including machine learning. To address this limitation, miRVim has been developed, providing a repository of human miRNA structures derived from both two-dimensional (MXFold2, CentroidFold, and RNAFold) and three-dimensional (RNAComposer and 3dRNA) structure prediction algorithms, in addition to experimentally available structures from the RCSB PDB repository. This data server aims to facilitate computational data analysis for drug discovery, opening new avenues for advancing technologies such as machine learning-based predictions in the field. The publicly accessible structures provided by miRVim, available athttps://mirna.in/miRVim, offer a valuable resource for the research community, advancing the field of miRNA-related computational analysis and drug discovery.
Patterns of physical activity in hunter-gatherer children compared with US and UK children
Authors: Kretschmer Luke , Dyble Mark , Chaudhary Nikhil , Bann David , Salali Gul Deniz 
Published: December 2023

AbstractSedentary lifestyles, mismatched with our active foraging history, contribute to escalating rates of non-communicable diseases. Contemporary hunter-gatherers appear to be highly active, but little is known about physical activity levels in hunter-gatherer children. We analysed 150 days of accelerometer data from 51 BaYaka hunter-gatherer children (aged 3-18) in the Republic of Congo, comparing it with British and American children (MCS and NHANES). BaYaka children were highly active, engaging in over 3 hours of moderate-to-vigorous physical activity (MVPA) daily, surpassing British adolescents by over 70 minutes. In US children activity declined with age; while in BaYaka children activity increased with age, unaffected by gender. Reflecting their foraging lifestyle, activity patterns varied within and between days, yet all children consistently rose with the sun. These findings highlight the impact of a foraging upbringing on children’s activity levels, providing a benchmark for understanding childhood physical activity and wellbeing.
Strawberry phenotypic plasticity in flowering time is driven by interaction between genetic loci and temperature
Authors: Prohaska Alexandre , Petit Aurélie , Lesemann Silke , Rey-Serra Pol , Mazzoni Luca , Masny Agnieszka , Sánchez-Sevilla José F. , Potier Aline , Gaston Amèlia , Klamkowski Krzysztof , Rothan Christophe , Mezzetti Bruno , Amaya Iraida , Olbricht Klaus , Denoyes Béatrice 
Published: December 2023

AbstractThe flowering time, which determines when the fruits or seeds can be harvested, is known to be sensitive to plasticity, i.e. the ability of a genotype to display different phenotypes in response to environmental variations. In the context of climate change, strawberry breeding can take advantage of phenotypic plasticity to create high-performing varieties adapted either to local conditions or to a wide range of climates. To decipher how the environment affects the genetic architecture of flowering time in cultivated strawberry (Fragaria ×ananassa) and modify its QTL effects, we used a bi-parental segregating population grown for two years at widely divergent latitudes (5 European countries) and combined climatic variables with genomic data (Affymetrix® SNP array). We detected 10 unique flowering time QTL and demonstrated that temperature modulates the effect of plasticity-related QTL. We propose candidate genes for the three main plasticity QTL, includingFaTFL1which is the most relevant candidate in the interval of the major temperature-sensitive QTL (6D_M). We further designed and validated a genetic marker for the 6D_M QTL which offers great potential for breeding programs, for example for selecting of early-flowering strawberry varieties well adapted to different environmental conditions.HighlightsA GXE study of a segregating strawberry population in Europe showed that temperature is the main driver of flowering time plasticity. A genetic marker was designed for the main QTL.
Synthetic mucus barrier arrays as a nanoparticle formulation screening platform
Authors: Zou Harry , Boboltz Allison , Cheema Yahya , Song Daniel , Duncan Gregg A. 
Published: December 2023

ABSTRACTA mucus gel layer lines the luminal surface of tissues throughout the body to protect them from infectious agents and particulates. As a result, nanoparticle drug delivery systems delivered to these sites may become trapped in mucus and subsequently cleared before they can reach target cells. As such, optimizing the properties of nanoparticle delivery vehicles, such as their surface chemistry and size, is essential to improving their penetration through the mucus barrier. In previous work, we developed a mucin-based hydrogel that has viscoelastic properties like that of native mucus which can be further tailored to mimic specific mucosal tissues and disease states. Using this biomimetic hydrogel system, a 3D-printed array containing synthetic mucus barriers was created that is compatible with a 96-well plate enabling its use as a high-throughput screening platform for nanoparticle drug delivery applications. To validate this system, we evaluated several established design parameters to determine their impact on nanoparticle penetration through synthetic mucus barriers. Consistent with the literature, we found nanoparticles of smaller size and coated with a protective PEG layer more efficiently penetrated through synthetic mucus barriers. In addition, we evaluated a mucolytic (tris (2-carboxyethyl) phosphine, TCEP) for use as a permeation enhancer for mucosal drug delivery. In comparison to N-acetyl cysteine (NAC), we found TCEP significantly improved nanoparticle penetration through a disease-like synthetic mucus barrier. Overall, our results establish a new high-throughput screening approach using synthetic mucus barrier arrays to identify promising nanoparticle formulation strategies for drug delivery to mucosal tissues.
Top-down perceptual inference shaping the activity of early visual cortex
Authors: Csikor Ferenc , Meszéna Balázs , Ócsai Katalin , Orbán Gergő 
Published: December 2023

AbstractDeep discriminative models provide remarkable insights into hierarchical processing in the brain by predicting neural activity along the visual pathway. However, these models differ from biological systems in their computational and architectural properties. Unlike biological systems, they require teaching signals for supervised learning. Moreover, they rely on feed-forward processing of stimuli, which contrasts with the extensive top-down connections in the ventral pathway. Here, we address both issues by developing a hierarchical deep generative model and show that it predicts an extensive set of experimental results in the primary and secondary visual cortices (V1 and V2). We show that the widely documented sensitivity of V2 neurons to textures is a consequence of learning a hierarchical representation of natural images. Further, we show that top-down influences are inherent to hierarchical inference. Hierarchical inference explains neural signatures of top-down interactions and reveals how higher-level representation shapes low-level representations through modulation of response mean and noise correlations in V1.
Elucidating the molecular determinants for binding modes of a third-generation HIV-1 integrase strand transfer inhibitor: Importance of side chain and solvent reorganization
Authors: Sun Qinfang , Biswas Avik , Lyumkis Dmitry , Levy Ronald , Deng Nanjie 
Published: December 2023

AbstractThe first and second-generation clinically used HIV-1 integrase (IN) strand transfer inhibitors (INSTIs) are key components of antiretroviral therapy (ART), which work by blocking the integration step in the HIV-1 replication cycle that is catalyzed by a nucleoprotein assembly called an intasome. However, resistance to even the latest clinically used INSTIs is beginning to emerge. Developmental third-generation INSTIs, based on naphthyridine scaffold, are promising candidates to combat drug-resistant viral variants. Among these novel INSTIs, compound 4f exhibits two distinct conformations when binding to intasomes from HIV-1 and the closely related prototype foamy virus (PFV), despite the high structural similarity of their INSTI binding pockets. The molecular mechanism and the key active site residues responsible for these differing binding modes in closely related intasomes remain elusive. To unravel the molecular determinants governing the two distinct binding modes, we employ a novel molecular dynamics-based free energy approach that utilizes alchemical pathways to overcome the sampling challenges associated with transitioning between two ligand conformations within crowded environments along physical pathways. The calculated conformational free energies successfully recapitulate the experimentally observed binding mode preferences in the two viral intasomes. Analysis of the simulated structures suggests that the observed binding mode preferences are caused by amino acid residue differences in both the front and the central catalytic sub-pocket of the INSTI binding site in HIV-1 and PFV. Additional free energy calculations on mutants of HIV-1 and PFV revealed that while both sub-pockets contribute to the binding mode selection, the central sub-pocket plays a more important role. These results highlight the importance of both side chain and solvent reorganization, as well as the conformational entropy in determining the ligand binding mode and will help inform the development of more effective INSTIs for combatting drug-resistant viral variants.
MHC-Fine: Fine-tuned AlphaFold for Precise MHC-Peptide Complex Prediction
Authors: Glukhov Ernest , Kalitin Dmytro , Stepanenko Darya , Zhu Yimin , Nguyen Thu , Jones George , Simmerling Carlos , Mitchell Julie C. , Vajda Sandor , Dill Ken A. , Padhorny Dzmitry , Kozakov Dima 
Published: December 2023

AbstractThe precise prediction of Major Histocompatibility Complex (MHC)-peptide complex structures is pivotal for understanding cellular immune responses and advancing vaccine design. In this study, we enhanced AlphaFold’s capabilities by fine-tuning it with a specialized dataset comprised by exclusively high-resolution MHC-peptide crystal structures. This tailored approach aimed to address the generalist nature of AlphaFold’s original training, which, while broad-ranging, lacked the granularity necessary for the high-precision demands of MHC-peptide interaction prediction. A comparative analysis was conducted against the homology-modeling-based method Pandora [13], as well as the AlphaFold multimer model [8]. Our results demonstrate that our fine-tuned model outperforms both in terms of RMSD (median value is 0.65 Å) but also provides enhanced predicted lDDT scores, offering a more reliable assessment of the predicted structures. These advances have substantial implications for computational immunology, potentially accelerating the development of novel therapeutics and vaccines by providing a more precise computational lens through which to view MHC-peptide interactions.