A Pleistocene legacy structures variation in modern seagrass ecosystems.

Distribution of Earth's biomes is structured by the match between climate and plant traits, which in turn shape associated communities and ecosystem processes and services. However, that climate-trait match can be disrupted by historical events, with lasting ecosystem impacts. As Earth's environment changes faster than at any time in human history, critical questions are whether and how organismal traits and ecosystems can adjust to altered conditions. We quantified the relative importance of current environmental forcing versus evolutionary history in shaping the growth form (stature and biomass) and associated community of eelgrass (Zostera marina), a widespread foundation plant of marine ecosystems along Northern Hemisphere coastlines, which experienced major shifts in distribution and genetic composition during the Pleistocene. We found that eelgrass stature and biomass retain a legacy of the Pleistocene colonization of the Atlantic from the ancestral Pacific range and of more recent within-basin bottlenecks and genetic differentiation. This evolutionary legacy in turn influences the biomass of associated algae and invertebrates that fuel coastal food webs, with effects comparable to or stronger than effects of current environmental forcing. Such historical lags in phenotypic acclimatization may constrain ecosystem adjustments to rapid anthropogenic climate change, thus altering predictions about the future functioning of ecosystems.

Development of a bottom-up coarse-grained model for interactions of lipids with TiO 2 nanoparticles.

Understanding interactions of inorganic nanoparticles with biomolecules is important in many biotechnology, nanomedicine, and toxicological research, however, the size of typical nanoparticles makes their direct modeling by atomistic simulations unfeasible. Here, we present a bottom-up coarse-graining approach for modeling titanium dioxide (TiO 2 ) nanomaterials in contact with phospholipids that uses the inverse Monte Carlo method to optimize the effective interactions from the structural data obtained in small-scale all-atom simulations of TiO 2 surfaces with lipids in aqueous solution. The resulting coarse-grained models are able to accurately reproduce the structural details of lipid adsorption on different titania surfaces without the use of an explicit solvent, enabling significant computational resource savings and favorable scaling. Our coarse-grained simulations show that small spherical TiO 2 nanoparticles ( r = 2 nm) can only be partially wrapped by a lipid bilayer with phosphoethanolamine headgroups, however, the lipid adsorption increases with the radius of the nanoparticle. The current approach can be used to study the effect of the size and shape of TiO 2 nanoparticles on their interactions with cell membrane lipids, which can be a determining factor in membrane wrapping as well as the recently discovered phenomenon of nanoquarantining, which involves the formation of layered nanomaterial-lipid structures.

Gravitational Raman Scattering in Effective Field Theory: A Scalar Tidal Matching at O(G

We present a framework to compute amplitudes for the gravitational analog of the Raman process, a quasielastic scattering of waves off compact objects, in worldline effective field theory. As an example, we calculate third post-Minkowskian order [O(G^{3})], or two-loop, phase shifts for the scattering of a massless scalar field including all tidal effects and dissipation. Our calculation unveils two sources of the classical renormalization-group flow of dynamical Love numbers: a universal running independent of the nature of the compact object, and a running self-induced by tides. Restricting to the black hole case, we find that our effective field theory phase shifts agree exactly with those from general relativity, provided that the relevant static Love numbers are set to zero. In addition, we carry out a complete matching of the leading scalar dynamical Love number required to renormalize a universal short scale divergence in the S wave. Our results pave the way for systematic calculations of gravitational Raman scattering at higher post-Minkowskian orders.

Inductive detection of temperature-induced magnetization dynamics of molecular spin systems.

The development and technological applications of molecular spin systems require versatile experimental techniques to characterize and control their static and dynamic magnetic properties. In the latter case, bulk spectroscopic and magnetometric techniques, such as AC magnetometry and pulsed electron paramagnetic resonance, are usually employed, showing high sensitivity, wide dynamic range, and flexibility. They are based on creating a nonequilibrium state either by changing the magnetic field or by applying resonant microwave radiation. Another possible source of perturbation is a laser pulse that rapidly heats the sample. This approach has proven to be one of the most useful techniques for studying the kinetics and mechanism of chemical and biochemical reactions. Inspired by these works, we propose an inductive detection of temperature-induced magnetization dynamics as applied to the study of molecular spin systems and describe the general design and construction of a particular induction probehead, taking into account the constraints imposed by the cryostat and electromagnet. To evaluate the performance, several coordination compounds of VO2+, Co2+, and Dy3+ were investigated using low-energy pulses of a terahertz free electron laser of the Novosibirsk free electron laser facility as a heat source. All measured magnetization dynamics were qualitatively or quantitatively described using a proposed basic theoretical model and compared with the data obtained by alternating current magnetometry. Based on the results of the research, the possible scope of applications of inductive detection and its advantages and disadvantages in comparison with standard methods are discussed.

A Review of the Use of Extracellular Vesicles in the Treatment of Neonatal Diseases: Current State and Problems with Translation to the Clinic.

Neonatal disorders, particularly those resulting from prematurity, pose a major challenge in health care and have a significant impact on infant mortality and long-term child health. The limitations of current therapeutic strategies emphasize the need for innovative treatments. New cell-free technologies utilizing extracellular vesicles (EVs) offer a compelling opportunity for neonatal therapy by harnessing the inherent regenerative capabilities of EVs. These nanoscale particles, secreted by a variety of organisms including animals, bacteria, fungi and plants, contain a repertoire of bioactive molecules with therapeutic potential. This review aims to provide a comprehensive assessment of the therapeutic effects of EVs and mechanistic insights into EVs from stem cells, biological fluids and non-animal sources, with a focus on common neonatal conditions such as hypoxic-ischemic encephalopathy, respiratory distress syndrome, bronchopulmonary dysplasia and necrotizing enterocolitis. This review summarizes evidence for the therapeutic potential of EVs, analyzes evidence of their mechanisms of action and discusses the challenges associated with the implementation of EV-based therapies in neonatal clinical practice.

Cognitive Impairment in Nonagenarians: Potential Metabolic Mechanisms Revealed by the Synergy of In Silico Gene Expression Modeling and Pathway Enrichment Analysis.

Previous studies examining the molecular and genetic basis of cognitive impairment, particularly in cohorts of long-living adults, have mainly focused on associations at the genome or transcriptome level. Dozens of significant dementia-associated genes have been identified, including APOE, APOC1, and TOMM40. However, most of these studies did not consider the intergenic interactions and functional gene modules involved in cognitive function, nor did they assess the metabolic changes in individual brain regions. By combining functional analysis with a transcriptome-wide association study, we aimed to address this gap and examine metabolic pathways in different areas of the brain of older adults. The findings from our previous genome-wide association study in 1155 older adults, 179 of whom had cognitive impairment, were used as input for the PrediXcan gene prediction algorithm. Based on the predicted changes in gene expression levels, we conducted a transcriptome-wide association study and functional analysis using the KEGG and HALLMARK databases. For a subsample of long-living adults, we used logistic regression to examine the associations between blood biochemical markers and cognitive impairment. The functional analysis revealed a significant association between cognitive impairment and the expression of NADH oxidoreductase in the cerebral cortex. Significant associations were also detected between cognitive impairment and signaling pathways involved in peroxisome function, apoptosis, and the degradation of lysine and glycan in other brain regions. Our approach combined the strengths of a transcriptome-wide association study with the advantages of functional analysis. It demonstrated that apoptosis and oxidative stress play important roles in cognitive impairment.

Mitochondrial Dysfunction in Dopaminergic Neurons Derived from Patients with LRRK2- and SNCA-Associated Genetic Forms of Parkinson's Disease.

Parkinson's disease (PD) is the second most common neurodegenerative disease. Some cases of PD may be caused by genetic factors, among which mutations in the LRRK2 and SNCA genes play an important role. To develop effective neuroprotective strategies for PD, it is important to diagnose the disease at the earliest stages of the neurodegenerative process. Therefore, the detection of diagnostic and prognostic markers of Parkinson's disease (PD) is an urgent medical need. Advances in induced pluripotent stem cell (iPSC) culture technology provide new opportunities for the search for new biomarkers of PD and its modeling in vitro. In our work, we used a new technology for multiplex profiling of gene expression using barcoding on the Nanostring platform to assess the activity of mitochondrial genes on iPSC-derived cultures of dopaminergic neurons obtained from patients with LRRK2- and SNCA-associated genetic forms PD and a healthy donor. Electron microscopy revealed ultrastructural changes in mitochondria in both LRRK2 and SNCA mutant cells, whereas mitochondria in cells from a healthy donor were normal. In a culture with the SNCA gene mutation, the ratio of the area occupied by mitochondria to the total area of the cytoplasm was significantly lower than in the control and in the line with the LRRK2 gene mutation. Transcriptome analysis of 105 mitochondria proteome genes using the Nanostring platform revealed differences between the diseased and normal cells in the activity of genes involved in respiratory complex function, the tricarboxylic acid cycle, ATP production, mitochondria-endoplasmic reticulum interaction, mitophagy, regulation of calcium concentration, and mitochondrial DNA replication.

Vanishing of Black Hole Tidal Love Numbers from Scattering Amplitudes.

We extract the black hole (BH) static tidal deformability coefficients (Love numbers) and their spin-0 and spin-1 analogs by comparing on-shell amplitudes for fields to scatter off a spinning BH in the worldline effective field theory and in general relativity. We point out that the general relativity amplitudes due to tidal effects originate entirely from the BH potential region. Thus, they can be separated from gravitational nonlinearities in the wave region, whose proper treatment requires higher order effective field theory loop calculations. In particular, the elastic scattering in the near field approximation is produced exclusively by tidal effects. We find this contribution to vanish identically, which implies that the static Love numbers of Kerr BHs are zero for all types of perturbations. We also reproduce the known behavior of scalar Love numbers for higher-dimensional BHs. Our results are manifestly gauge invariant and coordinate independent, thereby providing a valuable consistency check for the commonly used off-shell methods.

Filtration-based technologies for isolation, purification and analysis of extracellular vesicles.

The involvement of extracellular vesicles (EVs) in cellular communication with multifactorial and multifaceted biological activity has generated significant interest, highlighting their potential diagnostic and therapeutic applications. EVs are found in nearly all biological fluids creating a broad spectrum of where potential disease markers can be found for liquid biopsy development and what subtypes can be used for treatment of diseases. Complexity of biological fluids has generated a variety of different approaches for EV isolation and identification that may in one way or another be most optimal for research studies or clinical use. Each approach has its own advantages and disadvantages, significance of which can be evaluated depending on the end goal of the study. One of the methods is based on filtration which has received attention in the past years due its versatility, low cost and other advantages. Introduction of different approaches for EV capture and analysis that are based on filtration gave rise to new subcategories of filtration techniques which are presented in this overview. Miniaturization and combination of filtration-based approaches with microfluidics is also highlighted due its future prospects in healthcare, especially point-of-need technologies.

Neutron scattering study of polyamorphic THF·17(H2O) - toward a generalized picture of amorphous states and structures derived from clathrate hydrates.

From crystalline tetrahydrofuran clathrate hydrate, THF-CH (THF·17H2O, cubic structure II), three distinct polyamorphs can be derived. First, THF-CH undergoes pressure-induced amorphization when pressurized to 1.3 GPa in the temperature range 77-140 K to a form which, in analogy to pure ice, may be called high-density amorphous (HDA). Second, HDA can be converted to a densified form, VHDA, upon heat-cycling at 1.8 GPa to 180 K. Decompression of VHDA to atmospheric pressure below 130 K produces the third form, recovered amorphous (RA). Results from neutron scattering experiments and molecular dynamics simulations provide a generalized picture of the structure of amorphous THF hydrates with respect to crystalline THF-CH and liquid THF·17H2O solution (∼2.5 M). Although fully amorphous, HDA is heterogeneous with two length scales for water-water correlations (less dense local water structure) and guest-water correlations (denser THF hydration structure). The hydration structure of THF is influenced by guest-host hydrogen bonding. THF molecules maintain a quasiregular array, reminiscent of the crystalline state, and their hydration structure (out to 5 Å) constitutes ∼23H2O. The local water structure in HDA is reminiscent of pure HDA-ice featuring 5-coordinated H2O. In VHDA, the hydration structure of HDA is maintained but the local water structure is densified and resembles pure VHDA-ice with 6-coordinated H2O. The hydration structure of THF in RA constitutes ∼18 H2O molecules and the water structure corresponds to a strictly 4-coordinated network, as in the liquid. Both VHDA and RA can be considered as homogeneous.

Verification of Data from Supersensitive Detector of Hydrosphere Pressure Variations.

The paper describes experimental research and the results of these studies carried out in various bays of the Primorsky Territory of Russia using a supersensitive detector of hydrosphere pressure variations and a sound velocity profiler with pressure and temperature sensors. In all experiments, instruments, rigidly fixed to each other, were placed on the bottom at a depth of up to 10 m. Comparison of in-situ data from these instruments allowed us to experimentally calculate the coefficient of data conversion of the supersensitive detector of hydrosphere pressure variations when registering sea waves with periods ranging from several seconds to tens of minutes.

The biogeography of community assembly: latitude and predation drive variation in community trait distribution in a guild of epifaunal crustaceans.

While considerable evidence exists of biogeographic patterns in the intensity of species interactions, the influence of these patterns on variation in community structure is less clear. Studying how the distributions of traits in communities vary along global gradients can inform how variation in interactions and other factors contribute to the process of community assembly. Using a model selection approach on measures of trait dispersion in crustaceans associated with eelgrass (Zostera marina) spanning 30° of latitude in two oceans, we found that dispersion strongly increased with increasing predation and decreasing latitude. Ocean and epiphyte load appeared as secondary predictors; Pacific communities were more overdispersed while Atlantic communities were more clustered, and increasing epiphytes were associated with increased clustering. By examining how species interactions and environmental filters influence community structure across biogeographic regions, we demonstrate how both latitudinal variation in species interactions and historical contingency shape these responses. Community trait distributions have implications for ecosystem stability and functioning, and integrating large-scale observations of environmental filters, species interactions and traits can help us predict how communities may respond to environmental change.

Constraints on Single-Field Inflation from the BOSS Galaxy Survey.

Nonlocal primordial non-Gaussianity (NLPNG) is a smoking gun of interactions in single-field inflationary models and can be written as a combination of the equilateral and orthogonal templates. We present the first constraints on these from the redshift-space galaxy power spectra and bispectra of the BOSS data. These are the first such measurements independent of the cosmic microwave background fluctuations. We perform a consistent analysis that includes all necessary nonlinear corrections generated by NLPNG and vary all relevant cosmological and nuisance parameters in a global fit to the data. Our conservative analysis yields joint limits on the amplitudes of the equilateral and orthogonal shapes, f_{NL}^{equil}=940±600 and f_{NL}^{ortho}=-170±170 (both at 68% CL). These can be used to derive constraints on coefficients of the effective single-field inflationary Lagrangian; in particular, we find that the sound speed of inflaton fluctuations has the bound c_{s}≥0.013 at 95% CL. Fixing the quadratic galaxy bias and cosmological parameters, the constraints can be tightened to f_{NL}^{equil}=260±300 and f_{NL}^{ortho}=-23±120 (68% CL).

Structural Anomaly in Glasses: Molecular Dynamics Study of Organic Radical in Dibutylphthalate at Different Temperatures.

Understanding the heterogeneous nano/microscopic structures of various organic glasses is fundamental and necessary for many applications. Recently, unusual structural phenomena have been observed experimentally in various organic glasses near their glass transition temperatures (Tg), including dibutyl phthalate (DBP). In particular, the librational motion of radical probe in the glass is progressively suppressed upon temperature increase. In this work, we report in-depth molecular dynamics studies of structural anomalies in DBP glass, that revealed insights into the general mechanism of these phenomena. In particular, we have evidenced that the two types of solvation within alkyl chains coexist, allowing only small-angle wobbling of the solute molecule (TEMPO radical), and another favouring large-angle rotations. The former solvation assumes constrained location of the solute near carboxyl groups of DBP, while the latter is coupled to the concerted movement of butyl chains. Remarkably, excellent qualitative and quantitative agreement with previous experimental results were obtained. As such, we are certain that the above-mentioned dynamic phenomena explain the intriguing structural anomalies observed in DBP and some other glasses in the vicinity of Tg.

Biological Age Predictors: The Status Quo and Future Trends.

There is no single universal biomarker yet to estimate overall health status and longevity prospects. Moreover, a consensual approach to the very concept of aging and the means of its assessment are yet to be developed. Markers of aging could facilitate effective health control, more accurate life expectancy estimates, and improved health and quality of life. Clinicians routinely use several indicators that could be biomarkers of aging. Duly validated in a large cohort, models based on a combination of these markers could provide a highly accurate assessment of biological age and the pace of aging. Biological aging is a complex characteristic of chronological age (usually), health-to-age concordance, and medically estimated life expectancy. This study is a review of the most promising techniques that could soon be used in routine clinical practice. Two main selection criteria were applied: a sufficient sample size and reliability based on validation. The selected biological age calculators were grouped according to the type of biomarker used: (1) standard clinical and laboratory markers; (2) molecular markers; and (3) epigenetic markers. The most accurate were the calculators, which factored in a variety of biomarkers. Despite their demonstrated effectiveness, most of them require further improvement and cannot yet be considered for use in standard clinical practice. To illustrate their clinical application, we reviewed their use during the COVID-19 pandemic.

Active Pharmaceutical Ingredient-Ionic Liquids (API-ILs): Nanostructure of the Glassy State Studied by Electron Paramagnetic Resonance Spectroscopy.

Active Pharmaceutical Ingredient-Ionic Liquids (API-ILs) draw increasing interest as a particular class of ILs that possess unusual physicochemical properties along with simultaneous potentials for pharmaceutical applications. Although nanostructuring phenomena were actively investigated in common ILs, their studies in API-ILs are scarce so far. In this work, using the complex methodology of Electron Paramagnetic Resonance (EPR) and dissolved spin probes, we investigate nanostructuring phenomena in a series of API-ILs: [Cnmim][Ibu], [Cnmim][Gly], and [Cnmim][Sal] with n = 2, 4, and 6, respectively. We reveal similar trends for API-ILs and common ILs, as well as peculiarities inherent to the studied API-ILs. Unusual behavior observed for [Cnmim][Ibu] has been assigned to the presence of a non-polar fragment in the [Ibu]- anion, which leads to the formation of more complex nanostructures around the radical compared to common ILs. Understanding general trends in the formation of such self-organized molecular structures is of fundamental interest and importance for applying API-ILs.

Confinement of the Triplet States in π-Conjugated BODIPY Dimers Linked with Ethynylene or Butadiynylene Bridges: A Different View on the Effect of Symmetry.

Understanding the impact of the excited state wavefunction confinement is crucial for the engineering of the photophysical properties and applications of organic chromophores. In the present contribution, the localization of the triplet state wavefunctions of some symmetric ethyne/butadiyne bridged BODIPY dimers and asymmetric BODIPY derivatives presenting extended π-conjugation frameworks is studied with time-resolved electron paramagnetic resonance spectroscopy and time-dependent density functional theory computations. Based on the Zero Field Splitting D parameters, we conclude that the triplet state wavefunctions are highly localized on one BODIPY unit in the symmetric dimers, which is consistent with the ab initio modelling that finds delocalized triplet state destabilized by 12-14 kcal mol-1 as compared to its localized counterpart. The result provides a new insight into the study of triplet excited state confinement and the design of molecular wires or photosensitizers for photovoltaics and photocatalysis.

Pseudomonas aeruginosa efflux pump superfamily (review of literature).

The significant increase in the number of antibiotic-resistant microorganisms observed in recent years is a public health problem worldwide. One of the molecular mechanisms for the formation of antimicrobial resistance in bacteria is the presence of efflux pumps. The review presents an analysis of experimental studies related to the study of efflux pumps in clinical strains of Pseudomonas aeruginosa, one of the representatives of hospital pathogens of the ESKAPE group. This review is intended for specialists developing new types of drugs against antibiotic-resistant strains, as well as researchers studying the mechanisms of bacterial resistance to antibiotics, heavy metals, biocides and other antimicrobial factors.

Hidden Symmetry of Vanishing Love Numbers.

We show that perturbations of massless fields in a black hole background enjoy a hidden SL(2,R)×U(1) ("Love") symmetry in the properly defined near zone approximation. Love symmetry mixes low- and high-frequency modes. Still, this approximate symmetry allows us to derive exact results about static tidal responses. Generators of the Love symmetry are globally well defined for any value of black hole spin. Generic regular solutions of the near zone equation for linearized perturbations form infinite-dimensional SL(2,R) representations. In some special cases, these are highest weight representations. This situation corresponds to vanishing Love numbers. Other known facts about static Love numbers also acquire an elegant explanation in terms of the SL(2,R) representation theory.

Novel bioinformatics quality control metric for next-generation sequencing experiments in the clinical context.

As the use of next-generation sequencing (NGS) for the Mendelian diseases diagnosis is expanding, the performance of this method has to be improved in order to achieve higher quality. Typically, performance measures are considered to be designed in the context of each application and, therefore, account for a spectrum of clinically relevant variants. We present EphaGen, a new computational methodology for bioinformatics quality control (QC). Given a single NGS dataset in BAM format and a pre-compiled VCF-file of targeted clinically relevant variants it associates this dataset with a single arbiter parameter. Intrinsically, EphaGen estimates the probability to miss any variant from the defined spectrum within a particular NGS dataset. Such performance measure virtually resembles the diagnostic sensitivity of given NGS dataset. Here we present case studies of the use of EphaGen in context of BRCA1/2 and CFTR sequencing in a series of 14 runs across 43 blood samples and 504 publically available NGS datasets. EphaGen is superior to conventional bioinformatics metrics such as coverage depth and coverage uniformity. We recommend using this software as a QC step in NGS studies in the clinical context. Availability: https://github.com/m4merg/EphaGen or https://hub.docker.com/r/m4merg/ephagen.