Dissolved gases in the deep North Atlantic track ocean ventilation processes.

Gas exchange between the atmosphere and ocean interior profoundly impacts global climate and biogeochemistry. However, our understanding of the relevant physical processes remains limited by a scarcity of direct observations. Dissolved noble gases in the deep ocean are powerful tracers of physical air-sea interaction due to their chemical and biological inertness, yet their isotope ratios have remained underexplored. Here, we present high-precision noble gas isotope and elemental ratios from the deep North Atlantic (~32°N, 64°W) to evaluate gas exchange parameterizations using an ocean circulation model. The unprecedented precision of these data reveal deep-ocean undersaturation of heavy noble gases and isotopes resulting from cooling-driven air-to-sea gas transport associated with deep convection in the northern high latitudes. Our data also imply an underappreciated and large role for bubble-mediated gas exchange in the global air-sea transfer of sparingly soluble gases, including O2, N2, and SF6. Using noble gases to validate the physical representation of air-sea gas exchange in a model also provides a unique opportunity to distinguish physical from biogeochemical signals. As a case study, we compare dissolved N2/Ar measurements in the deep North Atlantic to physics-only model predictions, revealing excess N2 from benthic denitrification in older deep waters (below 2.9 km). These data indicate that the rate of fixed N removal in the deep Northeastern Atlantic is at least three times higher than the global deep-ocean mean, suggesting tight coupling with organic carbon export and raising potential future implications for the marine N cycle.

Examining linguistic shifts between preprints and publications.

Preprints allow researchers to make their findings available to the scientific community before they have undergone peer review. Studies on preprints within bioRxiv have been largely focused on article metadata and how often these preprints are downloaded, cited, published, and discussed online. A missing element that has yet to be examined is the language contained within the bioRxiv preprint repository. We sought to compare and contrast linguistic features within bioRxiv preprints to published biomedical text as a whole as this is an excellent opportunity to examine how peer review changes these documents. The most prevalent features that changed appear to be associated with typesetting and mentions of supporting information sections or additional files. In addition to text comparison, we created document embeddings derived from a preprint-trained word2vec model. We found that these embeddings are able to parse out different scientific approaches and concepts, link unannotated preprint-peer-reviewed article pairs, and identify journals that publish linguistically similar papers to a given preprint. We also used these embeddings to examine factors associated with the time elapsed between the posting of a first preprint and the appearance of a peer-reviewed publication. We found that preprints with more versions posted and more textual changes took longer to publish. Lastly, we constructed a web application (https://greenelab.github.io/preprint-similarity-search/) that allows users to identify which journals and articles that are most linguistically similar to a bioRxiv or medRxiv preprint as well as observe where the preprint would be positioned within a published article landscape.

Sal-type ABC-F proteins: intrinsic and common mediators of pleuromutilin resistance by target protection in staphylococci.

The first member of the pleuromutilin (PLM) class suitable for systemic antibacterial chemotherapy in humans recently entered clinical use, underscoring the need to better understand mechanisms of PLM resistance in disease-causing bacterial genera. Of the proteins reported to mediate PLM resistance in staphylococci, the least-well studied to date is Sal(A), a putative ABC-F NTPase that-by analogy to other proteins of this type-may act to protect the ribosome from PLMs. Here, we establish the importance of Sal proteins as a common source of PLM resistance across multiple species of staphylococci. Sal(A) is revealed as but one member of a larger group of Sal-type ABC-F proteins that vary considerably in their ability to mediate resistance to PLMs and other antibiotics. We find that specific sal genes are intrinsic to particular staphylococcal species, and show that this gene family is likely ancestral to the genus Staphylococcus. Finally, we solve the cryo-EM structure of a representative Sal-type protein (Sal(B)) in complex with the staphylococcal 70S ribosome, revealing that Sal-type proteins bind into the E site to mediate target protection, likely by displacing PLMs and other antibiotics via an allosteric mechanism.

Could simplified stimuli change how the brain performs visual search tasks? A deep neural network study.

Visual search is a complex behavior influenced by many factors. To control for these factors, many studies use highly simplified stimuli. However, the statistics of these stimuli are very different from the statistics of the natural images that the human visual system is optimized by evolution and experience to perceive. Could this difference change search behavior? If so, simplified stimuli may contribute to effects typically attributed to cognitive processes, such as selective attention. Here we use deep neural networks to test how optimizing models for the statistics of one distribution of images constrains performance on a task using images from a different distribution. We train four deep neural network architectures on one of three source datasets-natural images, faces, and x-ray images-and then adapt them to a visual search task using simplified stimuli. This adaptation produces models that exhibit performance limitations similar to humans, whereas models trained on the search task alone exhibit no such limitations. However, we also find that deep neural networks trained to classify natural images exhibit similar limitations when adapted to a search task that uses a different set of natural images. Therefore, the distribution of data alone cannot explain this effect. We discuss how future work might integrate an optimization-based approach into existing models of visual search behavior.

Rheology of Crystallizing LLDPE.

Polymer crystallization occurs in many plastic manufacturing processes, from injection molding to film blowing. Linear low-density polyethylene (LLDPE) is one of the most commonly processed polymers, wherein the type and extent of short-chain branching (SCB) may be varied to influence crystallization. In this work, we report simultaneous measurements of the rheology and Raman spectra, using a Rheo-Raman microscope, for two industrial-grade LLDPEs undergoing crystallization. These polymers are characterized by broad polydispersity, SCB and the presence of polymer chain entanglements. The rheological behavior of these entangled LLDPE melts is modeled as a function of crystallinity using a slip-link model. The partially crystallized melt is represented by a blend of linear chains with either free or crosslinked ends, wherein the crosslinks represent attachment to growing crystallites, and a modulus shift factor that increases with degree of crystallinity. In contrast to our previous application of the slip-link model to isotactic polypropylene (iPP), in which the introduction of only bridging segments with crosslinks at both ends was sufficient to describe the available data, for these LLDPEs we find it necessary to introduce dangling segments, with crosslinks at only one end. The model captures quantitatively the evolution of viscosity and elasticity with crystallization over the whole range of frequencies in the linear regime for two LLDPE grades.

Rapid Mapping of Dissolved Methane and Carbon Dioxide in Coastal Ecosystems Using the ChemYak Autonomous Surface Vehicle.

Coastal ecosystems host high levels of primary productivity leading to exceptionally dynamic elemental cycling in both water and sediments. In such environments, carbon is rapidly cycled leading to high rates of burial as organic matter and/or high rates of loss to the atmosphere and laterally to the coastal ocean in simpler forms, such as carbon dioxide (CO2) and methane (CH4). To better understand carbon cycling across these heterogeneous environments, new technologies beyond discrete sample collection and analysis are needed to characterize spatial and temporal variability. Here, we describe the ChemYak, an autonomous surface vehicle outfitted with a suite of in situ sensors, developed to achieve large spatial scale chemical mapping of these environments. Dissolved methane and carbon dioxide are measured by a laser spectrometer coupled to a gas extraction unit for continuous quantification during operation. The gas-powered vehicle is capable of rapidly surveying the coastal system with an endurance of up to 10 h at operating speeds in excess of 10 km h-1. Here, we demonstrate its ability to spatially characterize distributions of CO2, CH4, oxygen, and nitrate throughout a New England saltmarsh estuary.

Proteomic and Mutant Analysis of the CO2 Concentrating Mechanism of Hydrothermal Vent Chemolithoautotroph Thiomicrospira crunogena.

Many autotrophic microorganisms are likely to adapt to scarcity in dissolved inorganic carbon (DIC; CO2 + HCO3- + CO32-) with CO2 concentrating mechanisms (CCM) that actively transport DIC across the cell membrane to facilitate carbon fixation. Surprisingly, DIC transport has been well studied among cyanobacteria and microalgae only. The deep-sea vent gammaproteobacterial chemolithoautotroph Thiomicrospira crunogena has a low-DIC inducible CCM, though the mechanism for uptake is unclear, as homologs to cyanobacterial transporters are absent. To identify the components of this CCM, proteomes of T. crunogena cultivated under low- and high-DIC conditions were compared. Fourteen proteins, including those comprising carboxysomes, were at least 4-fold more abundant under low-DIC conditions. One of these proteins was encoded by Tcr_0854; strains carrying mutated copies of this gene, as well as the adjacent Tcr_0853, required elevated DIC for growth. Strains carrying mutated copies of Tcr_0853 and Tcr_0854 overexpressed carboxysomes and had diminished ability to accumulate intracellular DIC. Based on reverse transcription (RT)-PCR, Tcr_0853 and Tcr_0854 were cotranscribed and upregulated under low-DIC conditions. The Tcr_0853-encoded protein was predicted to have 13 transmembrane helices. Given the mutant phenotypes described above, Tcr_0853 and Tcr_0854 may encode a two-subunit DIC transporter that belongs to a previously undescribed transporter family, though it is widespread among autotrophs from multiple phyla.IMPORTANCE DIC uptake and fixation by autotrophs are the primary input of inorganic carbon into the biosphere. The mechanism for dissolved inorganic carbon uptake has been characterized only for cyanobacteria despite the importance of DIC uptake by autotrophic microorganisms from many phyla among the Bacteria and Archaea In this work, proteins necessary for dissolved inorganic carbon utilization in the deep-sea vent chemolithoautotroph T. crunogena were identified, and two of these may be able to form a novel transporter. Homologs of these proteins are present in 14 phyla in Bacteria and also in one phylum of Archaea, the Euryarchaeota Many organisms carrying these homologs are autotrophs, suggesting a role in facilitating dissolved inorganic carbon uptake and fixation well beyond the genus Thiomicrospira.

Inhibitory Effect of Adsorbed Water on the Transport of Methane in Carbon Nanotubes.

We investigate the transport diffusion of methane at 300 K and pressures of up to 15 bar in dry and wetted carbon nanotubes (CNTs) having diameters ranging from 0.95 to 2.034 nm using nonequilibrium molecular dynamics (NEMD) simulation. Because of their strong hydrogen bonding, preadsorbed water molecules transport in the form of clusters and block the diffusion of methane, reducing the Onsager coefficient of methane dramatically compared to that in dry CNTs. The reduction in the methane Onsager coefficient is greater in narrower CNTs or at higher water densities. Because the diameter of the water clusters is almost invariant with water density, the Onsager coefficient of water in the (10, 10) CNT increases linearly with water density. It is further found that whereas decreasing the CNT diameter from 2.034 to 0.95 nm enhances the Onsager coefficient of pure methane by about 1 order of magnitude, the Onsager coefficient of water is almost independent of the CNT diameter at a water density of 0.05 g/cm3. We propose a theoretical model for the strong dependency of methane diffusion in wetted CNTs on the Onsager coefficient of water, the preadsorbed water density, and the CNT diameter. The model predicts the Onsager coefficients of the methane/water mixture from the Onsager coefficients of the pure components. Our study provides a basic understanding of the coupled diffusion of immiscible components in nanochannels and will facilitate progress in gas storage and carbon capture as well as nanofiltration and biomedical and biotechnological applications.

Ancient origin of high taxonomic richness among insects.

Insects are a hyper-diverse group, comprising nearly three-quarters of all named animal species on the Earth, but the environmental drivers of their richness and the roles of ecological interactions and evolutionary innovations remain unclear. Previous studies have argued that family-level insect richness increased continuously over the evolutionary history of the group, but inclusion of extant family records artificially inflated the relative richness of younger time intervals. Here we apply sampling-standardization methods to a species-level database of fossil insect occurrences, removing biases present in previous richness curves. We show that insect family-richness peaked 125 Ma and that Recent values are only 1.5-3 times as high as the Late Palaeozoic. Rarefied species-richness data also tentatively suggest little or no net increase in richness over the past 125 Myr. The Cretaceous peak in family richness was coincident with major radiations within extant groups but occurred prior to extinctions within more basal groups. Those extinctions may in part be linked to mid-Cretaceous floral turnover following the evolution of flowering plants. Negligible net richness change over the past 125 Myr implies that major radiations within extant groups were offset by reduced richness within groups that are now relict or extinct.

Modelling the climatic niche of turtles: a deep-time perspective.

Ectotherms have close physiological ties with the thermal environment; consequently, the impact of future climate change on their biogeographic distributions is of major interest. Here, we use the modern and deep-time fossil record of testudines (turtles, tortoises, and terrapins) to provide the first test of climate on the niche limits of both extant and extinct (Late Cretaceous, Maastrichtian) taxa. Ecological niche models are used to assess niche overlap in model projections for key testudine ecotypes and families. An ordination framework is applied to quantify metrics of niche change (stability, expansion, and unfilling) between the Maastrichtian and present day. Results indicate that niche stability over evolutionary timescales varies between testudine clades. Groups that originated in the Early Cretaceous show climatic niche stability, whereas those diversifying towards the end of the Cretaceous display larger niche expansion towards the modern. Temperature is the dominant driver of modern and past distributions, whereas precipitation is important for freshwater turtle ranges. Our findings demonstrate that testudines were able to occupy warmer climates than present day in the geological record. However, the projected rate and magnitude of future environmental change, in concert with other conservation threats, presents challenges for acclimation or adaptation.

Analysis of nucleation using mean first-passage time data from molecular dynamics simulation.

We introduce a method for the analysis of nucleation using mean first-passage time (MFPT) statistics obtained by molecular dynamics simulation. The method is based on the Becker-Döring model for the dynamics of a nucleation-mediated phase change and rigorously accounts for the system size dependence of first-passage statistics. It is thus suitable for the analysis of systems in which the separation between time scales for nucleation and growth is small, due to either a small free energy barrier or a large system size. The method is made computationally practical by an approximation of the first-passage time distribution based on its cumulant expansion. Using this approximation, the MFPT of the model can be fit to data from molecular dynamics simulation in order to estimate valuable kinetic parameters, including the free energy barrier, critical nucleus size, and monomer attachment pre-factor, as well as the steady-state rates of nucleation and growth. The method is demonstrated using a case study on nucleation of n-eicosane crystals from the melt. For this system, we found that the observed distribution of first-passage times do not follow an exponential distribution at short times, rendering it incompatible with the assumptions made by some other methods. Using our method, the observed distribution of first-passage times was accurately described, and reasonable estimates for the kinetic parameters and steady-state rates of nucleation and growth were obtained.

Molecular simulation of flow-enhanced nucleation in n-eicosane melts under steady shear and uniaxial extension.

Non-equilibrium molecular dynamics is used to study crystal nucleation of n-eicosane under planar shear and, for the first time, uniaxial extension. A method of analysis based on the mean first-passage time is applied to the simulation results in order to determine the effect of the applied flow field type and strain rate on the steady-state nucleation rate and a characteristic growth rate, as well as the effects on kinetic parameters associated with nucleation: the free energy barrier, critical nucleus size, and monomer attachment pre-factor. The onset of flow-enhanced nucleation (FEN) occurs at a smaller critical strain rate in extension as compared to shear. For strain rates larger than the critical rate, a rapid increase in the nucleation rate is accompanied by decreases in the free energy barrier and critical nucleus size, as well as an increase in chain extension. These observations accord with a mechanism in which FEN is caused by an increase in the driving force for crystallization due to flow-induced entropy reduction. At high applied strain rates, the free energy barrier, critical nucleus size, and degree of stretching saturate, while the monomer attachment pre-factor and degree of orientational order increase steadily. This trend is indicative of a significant diffusive contribution to the nucleation rate under intense flows that is correlated with the degree of global orientational order in a nucleating system. Both flow fields give similar results for all kinetic quantities with respect to the reduced strain rate, which we define as the ratio of the applied strain rate to the critical rate. The characteristic growth rate increases with increasing strain rate, and shows a correspondence with the nucleation rate that does not depend on the type of flow field applied. Additionally, a structural analysis of the crystalline clusters indicates that the flow field suppresses the compaction and crystalline ordering of clusters, leading to the formation of large articulated clusters under strong flow fields, and compact well-ordered clusters under weak flow fields.

Next generation macrocyclic and acyclic cationic lipids for gene transfer: Synthesis and in vitro evaluation.

Previously we reported the synthesis and in vitro evaluation of four novel, short-chain cationic lipid gene delivery vectors, characterized by acyclic or macrocyclic hydrophobic regions composed of, or derived from, two 7-carbon chains. Herein we describe a revised synthesis of an expanded library of related cationic lipids to include extended chain analogues, their formulation with plasmid DNA (pDNA) and in vitro delivery into Chinese hamster ovarian (CHO-K1) cells. The formulations were evaluated against each other based on structural differences in the hydrophobic domain and headgroup. Structurally the library is divided into four sets based on lipids derived from two 7- or two 11-carbon hydrophobic chains, C7 and C11 respectively, which possess either a dimethylamine or a trimethylamine derived headgroup. Each set includes four cationic lipids based on an acyclic or macrocyclic, saturated or unsaturated hydrophobic domain. All lipids were co-formulated with the commercial cationic lipid 1,2-dimyristoyl-sn-glycero-3-ethylphosphocholine (EPC) in a 1:1 molar ratio, along with one of two distinct neutral co-lipids, cholesterol or 1,2-dioleoyl-sn-glycero-3-phosphoethanolamine (DOPE) in an overall cationic-to-neutral lipid molar ratio of 3:2. Binding of lipid formulations with DNA, and packing morphology associated with the individual lipid-DNA complexes were characterized by gel electrophoresis and small angle X-ray diffraction (SAXD), respectively. As a general trend, lipoplex formulations based on mismatched binary cationic lipids, composed of a shorter C7 lipid and the longer lipid EPC (C14), were generally associated with higher transfection efficiency and lower cytotoxicity than their more closely matched C11/EPC binary lipid formulation counterparts. Furthermore, the cyclic lipids gave transfection levels as high as or greater than their acyclic counterparts, and formulations with cholesterol exhibited higher transfection and lower cytotoxicity than those formulated with DOPE. A number of the lipid formulations with cholesterol as co-lipid performed as well as, or better than Lipofectamine 2000™ and EPC, the two positive controls employed in these studies. These results suggest that our novel cyclic and acyclic cationic lipid vectors are effective nonviral gene transfer agents that warrant further investigation.

Near-infrared silver cluster optically signaling oligonucleotide hybridization and assembling two DNA hosts.

Silver clusters with ~10 atoms form within DNA strands, and the conjugates are chemical sensors. The DNA host hybridizes with short oligonucleotides, and the cluster moieties optically respond to these analytes. Our studies focus on how the cluster adducts perturb the structure of their DNA hosts. Our sensor is comprised of an oligonucleotide with two components: a 5'-cluster domain that complexes silver clusters and a 3'-recognition site that hybridizes with a target oligonucleotide. The single-stranded sensor encapsulates an ~11 silver atom cluster with violet absorption at 400 nm and with minimal emission. The recognition site hybridizes with complementary oligonucleotides, and the violet cluster converts to an emissive near-infrared cluster with absorption at 730 nm. Our key finding is that the near-infrared cluster coordinates two of its hybridized hosts. The resulting tertiary structure was investigated using intermolecular and intramolecular variants of the same dimer. The intermolecular dimer assembles in concentrated (~5 µM) DNA solutions. Strand stoichiometries and orientations were chromatographically determined using thymine-modified complements that increase the overall conjugate size. The intramolecular dimer develops within a DNA scaffold that is founded on three linked duplexes. The high local cluster concentrations and relative strand arrangements again favor the antiparallel dimer for the near-infrared cluster. When the two monomeric DNA/violet cluster conjugates transform to one dimeric DNA/near-infrared conjugate, the DNA strands accumulate silver. We propose that these correlated changes in DNA structure and silver stoichiometry underlie the violet to near-infrared cluster transformation.

Fossil evidence for key innovations in the evolution of insect diversity.

Explaining the taxonomic richness of the insects, comprising over half of all described species, is a major challenge in evolutionary biology. Previously, several evolutionary novelties (key innovations) have been posited to contribute to that richness, including the insect bauplan, wings, wing folding and complete metamorphosis, but evidence over their relative importance and modes of action is sparse and equivocal. Here, a new dataset on the first and last occurrences of fossil hexapod (insects and close relatives) families is used to show that basal families of winged insects (Palaeoptera, e.g. dragonflies) show higher origination and extinction rates in the fossil record than basal wingless groups (Apterygota, e.g. silverfish). Origination and extinction rates were maintained at levels similar to Palaeoptera in the more derived Polyneoptera (e.g. cockroaches) and Paraneoptera (e.g. true bugs), but extinction rates subsequently reduced in the very rich group of insects with complete metamorphosis (Holometabola, e.g. beetles). Holometabola show evidence of a recent slow-down in their high net diversification rate, whereas other winged taxa continue to diversify at constant but low rates. These data suggest that wings and complete metamorphosis have had the most effect on family-level insect macroevolution, and point to specific mechanisms by which they have influenced insect diversity through time.

A silver cluster-DNA equilibrium.

DNA encapsulates silver clusters, and these hybrid nanomaterials form molecular sensors. We discuss a silver cluster-oligonucleotide sensor with four characteristics. First, a specific reporting cluster forms within a single-stranded DNA. This template uses the 5' cluster domain CCCCAACTCCTT with different 3' recognition sites for complementary oligonucleotides. The modular composite strand exclusively forms a cluster with λmax = 400 nm and with low emission. Conjugates were chromatographically purified, and their elemental analysis measured a cluster adduct with ∼11 silver atoms. Second, hybridization transforms the cluster. Size exclusion chromatography shows that the 3' recognition sites of the single-stranded conjugates hybridize with their complements. This secondary structural change both shifts cluster absorption from 400 to 490 nm and develops emission at 550 nm. Third, cluster size remains intact. Like their violet predecessors, purified blue-green clusters have ∼11 silver atoms. Cluster integrity is further supported by extracting the complement from the blue-green conjugate and reversing the spectral changes. Fourth, the cluster transformation is an equilibrium. Complementary strands generate an isosbestic point and thus directly link single-stranded hosts for the violet cluster and their hybridized analogs for the blue-green cluster. This equilibrium shifts with temperature. A van't Hoff analysis shows that longer and more stable duplexes favor the blue-green cluster. However, hybridized cluster hosts are less stable than their native DNA counterparts, and stability further degrades when short complements expose nucleobases within S1-S2. Duplex instability suggests that unpaired nucleobases coordinate the violet cluster and favor the single-stranded sensor. A balance between innate hybridization and exogenous folding highlights a distinct feature of silver clusters for sensing: they are both chromophoric reporters and ligands that modulate analyte-sensor interactions.

Silver clusters as both chromophoric reporters and DNA ligands.

Molecular silver clusters conjugated with DNA act as analyte sensors. Our studies evaluate a type of cluster-laden DNA strand whose structure and silver stoichiometry change with hybridization. The sensor strand integrates two functions: the 3' region binds target DNA strands through base recognition while the 5' sequence C(3)AC(3)AC(3)TC(3)A favors formation of a near-infrared absorbing and emitting cluster. This precursor form exclusively harbors an ∼11 silver atom cluster that absorbs at 400 nm and that condenses its single-stranded host. The 3' recognition site associates with a complementary target strand, thereby effecting a 330 nm red-shift in cluster absorption and a background-limited recovery of cluster emission at 790 nm. One factor underlying these changes is sensor unfolding and aggregation. Variations in salt and oligonucleotide concentrations control cluster development by influencing DNA association. Structural studies using fluorescence anisotropy, fluorescence correlation spectroscopy, and size exclusion chromatography show that the sensor-cluster conjugate opens and subsequently dimerizes with hybridization. A second factor contributing to the spectral and photophysical changes is cluster transformation. Empirical silver stoichiometries are preserved through hybridization, so hybridized, dimeric near-infrared conjugates host twice the amount of silver in relation to their violet absorbing predecessors. These DNA structure and net silver stoichiometry alterations provide insight into how DNA-silver conjugates recognize analytes.

Friction between solids and adsorbed fluids is spatially distributed at the nanoscale.

The widespread developments in the use of nanomaterials in catalysis, adsorption, and nanofluidics present significant new challenges in achieving optimal adsorbed fluid flow characteristics. Here we demonstrate, using molecular dynamics simulations of nanoconfined fluids, that at nanoscales, fluid-solid friction is not restricted to a sharp interface as is commonly assumed; instead it is distributed over the whole adsorbed fluid phase, and is strongest in an interfacial region that is not negligible in comparison to the system size. Our simulations yield position-dependent dynamical fluid-solid friction coefficients, and lead to a modification of conventional hydrodynamics, incorporating distributed momentum loss in the fluid due to fluid-solid interaction. The results demonstrate that the usual concepts of slip length or interfacial friction coefficient are meaningful only for uniform fluids, and lose their significance for adsorbates in nanospaces, which are intrinsically inhomogeneous. We show that static friction coefficients, based on equilibrium density distributions, follow the same spatial dependence as the dynamical coefficients. These results open up possibilities for tailoring nanomaterials and surfaces to engineer low friction pathways for adsorbed fluid flow by tuning the potential energy landscape.

Kinetic and Thermodynamic Control of G-Quadruplex Polymorphism by Na+ and K+ Cations.

G-Quadruplexes (G4s) are ubiquitous nucleic acid folding motifs that exhibit structural diversity that is dependent on cationic conditions. In this work, we exploit temperature-controlled single-molecule fluorescence resonance energy transfer (smFRET) to elucidate the kinetic and thermodynamic mechanisms by which monovalent cations (K+ and Na+) impact folding topologies for a simple G-quadruplex sequence (5'-GGG-(TAAGGG)3-3') with a three-state folding equilibrium. Kinetic measurements indicate that Na+ and K+ influence G4 formation in two distinctly different ways: the presence of Na+ modestly enhances an antiparallel G4 topology through an induced fit (IF) mechanism with a low affinity (Kd = 228 ± 26 mM), while K+ drives G4 into a parallel/hybrid topology via a conformational selection (CS) mechanism with much higher affinity (Kd = 1.9 ± 0.2 mM). Additionally, temperature-dependent studies of folding rate constants and equilibrium ratios reveal distinctly different thermodynamic driving forces behind G4 binding to K+ (ΔH°bind > 0, ΔS°bind > 0) versus Na+ (ΔH°bind < 0, ΔS°bind < 0), which further illuminates the diversity of the possible pathways for monovalent facilitation of G-quadruplex folding.

Changing word meanings in biomedical literature reveal pandemics and new technologies.

While we often think of words as having a fixed meaning that we use to describe a changing world, words are also dynamic and changing. Scientific research can also be remarkably fast-moving, with new concepts or approaches rapidly gaining mind share. We examined scientific writing, both preprint and pre-publication peer-reviewed text, to identify terms that have changed and examine their use. One particular challenge that we faced was that the shift from closed to open access publishing meant that the size of available corpora changed by over an order of magnitude in the last two decades. We developed an approach to evaluate semantic shift by accounting for both intra- and inter-year variability using multiple integrated models. This analysis revealed thousands of change points in both corpora, including for terms such as 'cas9', 'pandemic', and 'sars'. We found that the consistent change-points between pre-publication peer-reviewed and preprinted text are largely related to the COVID-19 pandemic. We also created a web app for exploration that allows users to investigate individual terms ( https://greenelab.github.io/word-lapse/ ). To our knowledge, our research is the first to examine semantic shift in biomedical preprints and pre-publication peer-reviewed text, and provides a foundation for future work to understand how terms acquire new meanings and how peer review affects this process.