We fit an extended distribution function (EDF) to K giants in the Sloan Extension for Galactic Understanding and Exploration survey. These stars are detected to radii ∼80 kpc and span a wide range in ...Fe/H. Our EDF, which depends on Fe/H in addition to actions, encodes the entanglement of metallicity with dynamics within the Galaxy's stellar halo. Our maximum-likelihood fit of the EDF to the data allows us to model the survey's selection function. The density profile of the K giants steepens with radius from a slope ∼−2 to ∼−4 at large radii. The halo's axis ratio increases with radius from 0.7 to almost unity. The metal-rich stars are more tightly confined in action space than the metal-poor stars and form a more flattened structure. A weak metallicity gradient ∼−0.001 dex kpc−1, a small gradient in the dispersion in Fe/H of ∼0.001 dex kpc−1, and a higher degree of radial anisotropy in metal-richer stars result. Lognormal components with peaks at ∼−1.5 and ∼−2.3 are required to capture the overall metallicity distribution, suggestive of the existence of two populations of K giants. The spherical anisotropy parameter varies between 0.3 in the inner halo to isotropic in the outer halo. If the Sagittarius stream is included, a very similar model is found but with a stronger degree of radial anisotropy throughout.
The distribution of Milky Way halo blue horizontal-branch (BHB) stars is examined using action-based extended distribution functions (EDFs) that describe the locations of stars in phase space, ...metallicity, and age. The parameters of the EDFs are fitted using stars observed in the Sloan Extension for Galactic Understanding and Exploration-II (SEGUE-II) survey that traces the phase-space kinematics and chemistry out to ~70 kpc. A maximum a posteriori probability (MAP) estimate method and a Markov Chain Monte Carlo method are applied, taking into account the selection function in positions, distance, and metallicity for the survey. The best-fitting EDF declines with actions less steeply at actions characteristic of the inner halo than at the larger actions characteristic of the outer halo, and older ages are found at smaller actions than at larger actions. In real space, the radial density profile steepens smoothly from -2 at ~2 kpc to -4 in the outer halo, with an axis ratio ~0.7 throughout. There is no indication for rotation in the BHBs, although this is highly uncertain. A moderate level of radial anisotropy is detected, with beta s varying from isotropic to between ~0.1 and ~0.3 in the outer halo depending on latitude. The BHB data are consistent with an age gradient of -0.03 Gyr kpc super( -1), with some uncertainty in the distribution of the larger ages. These results are consistent with a scenario in which older, larger systems contribute to the inner halo, whilst the outer halo primarily comprises younger, smaller systems.
Abstract
Industrial wastewaters laden with toxic dyes are required to be treated prior to their disposal in view of their adverse effect on human health and aquatic ecosystems. Thus in this research, ...CaFe2O4 nanoparticles were prepared and used as adsorbent for elimination of reactive orange 12 dye (RO12) from aqueous medium. The CaFe2O4 nanoparticles exhibit specific surface area of ∼230 m2/g and average pore diameter of ∼2.5 nm. Maximum RO12 removal of 77% was observed at solution pH 2.0 with uptake capacity of 276.92 mg/g. The electrostatic interaction between CaFe2O4 nanoparticles and RO12 was the main driving force behind this adsorption. The kinetic modeling reveals that this adsorption process obeyed the pseudo-second-order kinetic model accurately (R2: 0.988–0.994), indicating chemisorption behavior. The adsorption experimental data firmly followed the Langmuir isotherm model (R2: 0.997), confirming monolayer adsorption. Thermodynamic study suggests that the adsorption process is spontaneous (ΔG0 = −8.76 to −3.19 kJ/mol) and exothermic in nature (ΔH0 = –71.86 kJ). A neural network model (optimum topology of 4–7–1) was developed for precise forecasting of RO12 removal (%). The developed model with very high correlation coefficient (0.986) and very low mean squared error (0.00185) was successful for accurate prediction of experimental data.
The de novo design of antimicrobial therapeutics involves the exploration of a vast chemical repertoire to find compounds with broad-spectrum potency and low toxicity. Here, we report an efficient ...computational method for the generation of antimicrobials with desired attributes. The method leverages guidance from classifiers trained on an informative latent space of molecules modelled using a deep generative autoencoder, and screens the generated molecules using deep-learning classifiers as well as physicochemical features derived from high-throughput molecular dynamics simulations. Within 48 days, we identified, synthesized and experimentally tested 20 candidate antimicrobial peptides, of which two displayed high potency against diverse Gram-positive and Gram-negative pathogens (including multidrug-resistant Klebsiella pneumoniae) and a low propensity to induce drug resistance in Escherichia coli. Both peptides have low toxicity, as validated in vitro and in mice. We also show using live-cell confocal imaging that the bactericidal mode of action of the peptides involves the formation of membrane pores. The combination of deep learning and molecular dynamics may accelerate the discovery of potent and selective broad-spectrum antimicrobials.
Alzheimer's disease (AD) is characterized by deposition of amyloid beta (Aβ) peptides into senile plaques in the brain. While most familial mutations are associated with early-onset AD, recent ...studies report the AD-protective nature of two genetic human Aβ variants, i.e. A2T and A2V, in the heterozygous state. The mixture of A2V Aβ1-6 (Aβ
) hexapeptide and WT Aβ1-42 (Αβ
) is also found neuroprotective. Motivated by these findings, in this study we investigate the effects of WT, A2V, and A2T Aβ
hexapeptide binding on the monomeric WT Aβ
landscape. For this purpose, we have performed extensive atomistic Replica Exchange Molecular Dynamics simulations, elucidating preferential binding of Aβ
with the A2V and A2T hexapeptides compared to WT Aβ
. A notable reorganization of the Aβ
landscape is revealed due to hexapeptide association, as manifested by lowering of transient interactions between the central and C-terminal hydrophobic patches. Concurrently, Aβ
-bound Aβ
monomer exhibits alternative structural features that are strongly dependent on the hexapeptide sequence. For example, a central helix is more frequently populated within the A2T-bound monomer, while A2V-bound Aβ
is often enhanced in overall disorder. Taken together, the present simulations offer novel molecular insights onto the effect of the N-terminal hexapeptide binding on the Aβ
monomer structure, which might help in explaining their reported amyloid inhibition properties.
We present results from atomistic molecular dynamics simulations to characterize the effects of cosolvents, such as urea and guanidinium (Gdm) salts, on the water confined in hydrophobic carbon ...nanotubes. We observed complete drying of the nanotube interiors of diameter ranging from 8 to 17 Å in urea. In contrast, the water population within nanotube cores smaller than 12 Å remains unaffected in GdmCl solution, whereas larger nanotube interiors become partially dehydrated with prevailing presence of stable Gdm(+)-Gdm(+) dimers. The molecular arrangement and the lifetime inside the nanotube were found to be characteristics of a particular cosolvent. In both urea and GdmCl solutions, preferential cosolvent intrusion resulting in nanotube dehydration is driven by the stronger dispersion interaction of cosolvent than water with the nanotube. The partial drying of the hydrophobic core is attributed to guanidinium's better hydration and weaker self-association propensity compared to urea, as well as to its moderate ion-pairing with strongly hydrated chloride ions. The Gdm(+) induced dehydration varies with the charge density of counter-ions, as the presence of high charge-density sulfate ions impedes penetration of guanidinium, and consequent dehydration of the nanotube. These findings provide important insights into the effect of cosolvents on the nano-confined water in a hydrophobic environment.
ABSTRACT
Understanding the assembly of our Galaxy requires us to also characterize the systems that helped build it. In this work, we accomplish this by exploring the chemistry of accreted halo stars ...from Gaia-Enceladus/Gaia-Sausage (GES) selected in the infrared from the Apache Point Observatory Galactic Evolution Experiment (APOGEE) Data Release 16. We use high resolution optical spectra for 62 GES stars to measure abundances in 20 elements spanning the α, Fe-peak, light, odd-Z, and notably, the neutron-capture groups of elements to understand their trends in the context of and in contrast to the Milky Way and other stellar populations. Using these derived abundances we find that the optical and the infrared abundances agree to within 0.15 dex except for O, Co, Na, Cu, and Ce. These stars have enhanced neutron-capture abundance trends compared to the Milky Way, and their Eu/Mg and neutron-capture abundance ratios (e.g. Y/Eu, Ba/Eu, Zr/Ba, La/Ba, and Nd/Ba) point to r-process enhancement and a delay in s-process enrichment. Their α/Fe trend is lower than the Milky Way trend for Fe/H > −1.5 dex, similar to previous studies of GES stars and consistent with the picture that these stars formed in a system with a lower rate of star formation. This is further supported by their depleted abundances in Ni, Na, and Cu abundances, again, similar to previous studies of low-α stars with accreted origins.
The prevalent eye disease age-onset cataract is associated with aggregation of human γD-crystallins, one of the longest-lived proteins. Identification of the γ-crystallin precursors to aggregates is ...crucial for developing strategies to prevent and reverse cataract. Our microseconds of atomistic molecular dynamics simulations uncover the molecular structure of the experimentally detected aggregation-prone folding intermediate species of monomeric native γD-crystallin with a largely folded C-terminal domain and a mostly unfolded N-terminal domain. About 30 residues including a, b, and c strands from the Greek Key motif 4 of the C-terminal domain experience strong solvent exposure of hydrophobic residues as well as partial unstructuring upon N-terminal domain unfolding. Those strands comprise the domain—domain interface crucial for unusually high stability of γD-crystallin. We further simulate the intermolecular linkage of these monomeric aggregation precursors, which reveals domain-swapped dimeric structures. In the simulated dimeric structures, the N-terminal domain of one monomer is frequently found in contact with residues 135–164 encompassing the a, b, and c strands of the Greek Key motif 4 of the second molecule. The present results suggest that γD-crystallin may polymerize through successive domain swapping of those three C-terminal β-strands leading to age-onset cataract, as an evolutionary cost of its very high stability. Alanine substitutions of the hydrophobic residues in those aggregation-prone β-strands, such as L145 and M147, hinder domain swapping as a pathway toward dimerization. These findings thus provide critical molecular insights onto the initial stages of age-onset cataract, which is important for understanding protein aggregation diseases.
Explainable machine learning for molecular toxicity prediction is a promising approach for efficient drug development and chemical safety. A predictive ML model of toxicity can reduce experimental ...cost and time while mitigating ethical concerns by significantly reducing animal and clinical testing. Herein, we use a deep learning framework for simultaneously modeling in vitro, in vivo, and clinical toxicity data. Two different molecular input representations are used; Morgan fingerprints and pre-trained SMILES embeddings. A multi-task deep learning model accurately predicts toxicity for all endpoints, including clinical, as indicated by the area under the Receiver Operator Characteristic curve and balanced accuracy. In particular, pre-trained molecular SMILES embeddings as input to the multi-task model improved clinical toxicity predictions compared to existing models in MoleculeNet benchmark. Additionally, our multitask approach is comprehensive in the sense that it is comparable to state-of-the-art approaches for specific endpoints in in vitro, in vivo and clinical platforms. Through both the multi-task model and transfer learning, we were able to indicate the minimal need of in vivo data for clinical toxicity predictions. To provide confidence and explain the model's predictions, we adapt a post-hoc contrastive explanation method that returns pertinent positive and negative features, which correspond well to known mutagenic and reactive toxicophores, such as unsubstituted bonded heteroatoms, aromatic amines, and Michael receptors. Furthermore, toxicophore recovery by pertinent feature analysis captures more of the in vitro (53%) and in vivo (56%), rather than of the clinical (8%), endpoints, and indeed uncovers a preference in known toxicophore data towards in vitro and in vivo experimental data. To our knowledge, this is the first contrastive explanation, using both present and absent substructures, for predictions of clinical and in vivo molecular toxicity.
Since ancient times, most of the world’s civilization flourished along the banks of rivers and the coastal region. So the coastal region plays a vital role for human economic activities as well as ...their livelihood. The Kanthi coast, the northernmost part of the North Circus coast of India stretches in West Bengal and northern Odisha. The 45 km stretched coast land is associated with a dense population and faces the tropical cyclone emerging from the Bay of Bengal. The prime objective of the paper is to assess the coastal vulnerability of the study area. With the help of several indicators, viz. shoreline change rate, rate of sea level change, slope of the beach, wave height, tidal range, regional elevation, geomorphic features, sediment properties, coastal regulation zone (CRZ) violation ratio, the research work assess the Coastal Vulnerability Zone (CVZ) of the Kanthi Coastal region. The weightage sum method and Coastal Vulnerability Index (CVI) are being used. From this research work, it has been revealed that the western segment especially, Digha and Shankarpur are experiencing a high vulnerability situation.
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