Moldable Plastics (Polycaprolactone) can be Acutely Toxic to Developing Zebrafish and Activate Nuclear Receptors in Mammalian Cells.

Popularized on social media, hand-moldable plastics are formed by consumers into tools, trinkets, and dental prosthetics. Despite the anticipated dermal and oral contact, manufacturers share little information with consumers about these materials, which are typically sold as microplastic-sized resin pellets. Inherent to their function, moldable plastics pose a risk of dermal and oral exposure to unknown leachable substances. We analyzed 12 moldable plastics advertised for modeling and dental applications and determined them to be polycaprolactone (PCL) or thermoplastic polyurethane (TPU). The bioactivities of the most popular brands advertised for modeling applications of each type of polymer were evaluated using a zebrafish embryo bioassay. While water-borne exposure to the TPU pellets did not affect the targeted developmental end points at any concentration tested, the PCL pellets were acutely toxic above 1 pellet/mL. The aqueous leachates of the PCL pellets demonstrated similar toxicity. Methanolic extracts from the PCL pellets were assayed for their bioactivity using the Attagene FACTORIAL platform. Of the 69 measured end points, the extracts activated nuclear receptors and transcription factors for xenobiotic metabolism (pregnane X receptor, PXR), lipid metabolism (peroxisome proliferator-activated receptor γ, PPARγ), and oxidative stress (nuclear factor erythroid 2-related factor 2, NRF2). By nontargeted high-resolution comprehensive two-dimensional gas chromatography (GC × GC-HRT), we tentatively identified several compounds in the methanolic extracts, including PCL oligomers, a phenolic antioxidant, and residues of suspected antihydrolysis and cross-linking additives. In a follow-up zebrafish embryo bioassay, because of its stated high purity, biomedical grade PCL was tested to mitigate any confounding effects due to chemical additives in the PCL pellets; it elicited comparable acute toxicity. From these orthogonal and complementary experiments, we suggest that the toxicity was due to oligomers and nanoplastics released from the PCL rather than chemical additives. These results challenge the perceived and assumed inertness of plastics and highlight their multiple sources of toxicity.

Synergism of primary and secondary interactions in a crystalline hydrogen peroxide complex with tin.

Despite the significance of H2O2-metal adducts in catalysis, materials science and biotechnology, the nature of the interactions between H2O2 and metal cations remains elusive and debatable. This is primarily due to the extremely weak coordinating ability of H2O2, which poses challenges in characterizing and understanding the specific nature of these interactions. Herein, we present an approach to obtain H2O2-metal complexes that employs neat H2O2 as both solvent and ligand. SnCl4 effectively binds H2O2, forming a SnCl4(H2O2)2 complex, as confirmed by 119Sn and 17O NMR spectroscopy. Crystalline adducts, SnCl4(H2O2)2·H2O2·18-crown-6 and 2[SnCl4(H2O2)(H2O)]·18-crown-6, are isolated and characterized by X-ray diffraction, providing the complete characterization of the hydrogen bonding of H2O2 ligands including geometric parameters and energy values. DFT analysis reveals the synergy between a coordinative bond of H2O2 with metal cation and its hydrogen bonding with a second coordination sphere. This synergism of primary and secondary interactions might be a key to understanding H2O2 reactivity in biological systems.

Dioxygen-halogen bonding exemplified by crystalline peroxosolvates of N,N'-bis(haloacetyl) bispidines.

The halogen bonding in molecular crystals and supramolecular assemblies has been widely investigated. Special attention is given to the molecular structures capable of simultaneously exhibiting different types of non-covalent interactions, including conventional hydrogen bonds and halogen bonds. This paper systematically analyzes crystalline peroxosolvates of bispidine-based bis-amide derivatives, containing haloacetic acid residues, namely previously reported 1,1'-(1,5-dimethyl-3,7-diazabicyclo[3.3.1]nonane-3,7-diyl)bis(2-iodooethanone) peroxosolvate C13H20I2N2O2·H2O2 (1) and four new crystalline compounds, 1,1'-(1,5-dimethyl-3,7-diazabicyclo[3.3.1]nonane-3,7-diyl)bis(2-bromoethanone) peroxosolvate C13H20Br2N2O2·H2O2 (2), 1,1'-(9-hydroperoxy-9-hydroxy-1,5-dimethyl-3,7-diazabicyclo[3.3.1]nonane-3,7-diyl)bis(2-iodoethanone) peroxosolvate C13H20I2N2O5·0.5H2O2 (3), 1,1'-(9-hydroperoxy-9-hydroxy-1,5-dimethyl-3,7-diazabicyclo[3.3.1]nonane-3,7-diyl)bis(2-bromoethanone) peroxosolvate C13H20Br2N2O5·H2O2 (4), and 1,1'-(9-hydroperoxy-9-hydroxy-1,5-dimethyl-3,7-diazabicyclo[3.3.1]nonane-3,7-diyl)bis(2-chloroethanone) peroxosolvate C13H20Cl2N2O5·H2O2 (5). Compounds 2-5 were synthesized for the first time and their crystal structures were determined by single-crystal X-ray diffractometry (SCXRD). To the best of our knowledge, 3-5 are unprecedented crystalline hydrogen peroxide adducts of organic hydroperoxides (R-OOH). Short intermolecular contacts between halogen and hydroperoxo oxygen atoms were found in 1-3. The halogen bonding of C-I(Br) fragments with dioxygen species in compounds 1-3 as well as in the previously reported cocrystal of diacetone diperoxide with triodotrinitrobenzene (6) was identified through reduced density gradient analysis, Hirshfeld surface analysis, and Bader analysis of crystalline electron density. The interactions were quantified using the electron density topological properties acquired from the periodic DFT calculations and evaluated to lie in the range of 9-19 kJ mol-1. A distinctive spectral feature was revealed for this type of interaction, involving a red shift of the characteristic O-O stretching vibration by about 6 cm-1, which appeared in IR spectra as a narrow low-intensity band in the region 837-872 cm-1.

Enhanced charge capacity and stability of Germanium(IV) Sulfide-Based anodes through Triton X100-Assisted synthesis and polysulfide shuttle mitigation.

Highly soluble germanium oxide,an amorphous macroreticular form of germanium oxide, was used as a precursor for the deposition of GeS2on reduced graphene oxide (rGO) through a low-temperature, wet-chemistry process. Thermal treatment of the solid provided an ultrathin rGO - supported amorphous GeS2coating. The GeS2@rGO composite was tested as a lithium ion battery (LIB) anode. Leveraging the versatility of wet chemistry processing, we employed strategies initially developed for mitigating polysulfide shuttle effects in lithium-sulfur batteries to enhance anode performance. The anode exhibited exceptional stability, surpassing 1000 cycles, with charge capacities exceeding 1220 and 870 mAh.g-1 at rates of 2 and 5 A.g-1, respectively. Performance improvements were achieved by minimizing GeS2 grain size using the non-ionic surfactant Triton X-100 during synthesis and preventing polysulfide shuttle effects through a negatively charged thick glass fiber separator, fluoroethylene carbonate additive (FEC) in EC:DEC (ethylene carbonate: diethyl carbonate) solvent, and a polyacrylic acid (PAA) binder. These cumulative modifications more than tripled the charge capacity of the germanium sulfide LIB anode. Feasibility was further demonstrated through full cell studies using a LiCoO2 counter electrode.

A community effort in SARS-CoV-2 drug discovery.

The COVID-19 pandemic continues to pose a substantial threat to human lives and is likely to do so for years to come. Despite the availability of vaccines, searching for efficient small-molecule drugs that are widely available, including in low- and middle-income countries, is an ongoing challenge. In this work, we report the results of an open science community effort, the "Billion molecules against COVID-19 challenge", to identify small-molecule inhibitors against SARS-CoV-2 or relevant human receptors. Participating teams used a wide variety of computational methods to screen a minimum of 1 billion virtual molecules against 6 protein targets. Overall, 31 teams participated, and they suggested a total of 639,024 molecules, which were subsequently ranked to find 'consensus compounds'. The organizing team coordinated with various contract research organizations (CROs) and collaborating institutions to synthesize and test 878 compounds for biological activity against proteases (Nsp5, Nsp3, TMPRSS2), nucleocapsid N, RdRP (only the Nsp12 domain), and (alpha) spike protein S. Overall, 27 compounds with weak inhibition/binding were experimentally identified by binding-, cleavage-, and/or viral suppression assays and are presented here. Open science approaches such as the one presented here contribute to the knowledge base of future drug discovery efforts in finding better SARS-CoV-2 treatments.

Bayesian monitoring of COVID-19 in Sweden.

In an effort to provide regional decision support for the public healthcare, we design a data-driven compartment-based model of COVID-19 in Sweden. From national hospital statistics we derive parameter priors, and we develop linear filtering techniques to drive the simulations given data in the form of daily healthcare demands. We additionally propose a posterior marginal estimator which provides for an improved temporal resolution of the reproduction number estimate as well as supports robustness checks via a parametric bootstrap procedure. From our computational approach we obtain a Bayesian model of predictive value which provides important insight into the progression of the disease, including estimates of the effective reproduction number, the infection fatality rate, and the regional-level immunity. We successfully validate our posterior model against several different sources, including outputs from extensive screening programs. Since our required data in comparison is easy and non-sensitive to collect, we argue that our approach is particularly promising as a tool to support monitoring and decisions within public health. Significance: Using public data from Swedish patient registries we develop a national-scale computational model of COVID-19. The parametrized model produces valuable weekly predictions of healthcare demands at the regional level and validates well against several different sources. We also obtain critical epidemiological insights into the disease progression, including, e.g., reproduction number, immunity and disease fatality estimates. The success of the model hinges on our novel use of filtering techniques which allows us to design an accurate data-driven procedure using data exclusively from healthcare demands, i.e., our approach does not rely on public testing and is therefore very cost-effective.

Jupiter Science Enabled by ESA's Jupiter Icy Moons Explorer.

ESA's Jupiter Icy Moons Explorer (JUICE) will provide a detailed investigation of the Jovian system in the 2030s, combining a suite of state-of-the-art instruments with an orbital tour tailored to maximise observing opportunities. We review the Jupiter science enabled by the JUICE mission, building on the legacy of discoveries from the Galileo, Cassini, and Juno missions, alongside ground- and space-based observatories. We focus on remote sensing of the climate, meteorology, and chemistry of the atmosphere and auroras from the cloud-forming weather layer, through the upper troposphere, into the stratosphere and ionosphere. The Jupiter orbital tour provides a wealth of opportunities for atmospheric and auroral science: global perspectives with its near-equatorial and inclined phases, sampling all phase angles from dayside to nightside, and investigating phenomena evolving on timescales from minutes to months. The remote sensing payload spans far-UV spectroscopy (50-210 nm), visible imaging (340-1080 nm), visible/near-infrared spectroscopy (0.49-5.56 µm), and sub-millimetre sounding (near 530-625 GHz and 1067-1275 GHz). This is coupled to radio, stellar, and solar occultation opportunities to explore the atmosphere at high vertical resolution; and radio and plasma wave measurements of electric discharges in the Jovian atmosphere and auroras. Cross-disciplinary scientific investigations enable JUICE to explore coupling processes in giant planet atmospheres, to show how the atmosphere is connected to (i) the deep circulation and composition of the hydrogen-dominated interior; and (ii) to the currents and charged particle environments of the external magnetosphere. JUICE will provide a comprehensive characterisation of the atmosphere and auroras of this archetypal giant planet.

Bioinspired Non-Heme Mn Catalysts for Regio- and Stereoselective Oxyfunctionalizations with H2 O2.

In recent years, metalloenzymes-mediated highly selective oxidations of organic substrates under mild conditions have been inspiration for developing synthetic bioinspired catalyst systems, capable of conducting such processes in the laboratory (and, in the future, in industry), relying on easy-to-handle and environmentally benign oxidants such as H2 O2 . To date, non-heme manganese complexes with chiral bis-amino-bis-pyridylmethyl and structurally related ligands are considered as possessing the highest synthetic potential, having demonstrated the ability to mediate a variety of chemo- and stereoselective oxidative transformations, such as epoxidations, C(sp3 )-H hydroxylations and ketonizations, oxidative desymmetrizations, kinetic resolutions, etc. Furthermore, in the past few years non-heme Mn based catalysts have become the major platform for studies focused on getting insight into the molecular mechanisms of oxidant activation and (stereo)selective oxygen transfer, testing non-traditional hydroperoxide oxidants, engineering catalytic sites with enzyme-like substrate recognition-based selectivity, exploration of catalytic regioselectivity trends in the oxidation of biologically active substrates of natural origin. This contribution summarizes the progress in manganese catalyzed C-H oxygenative transformations of organic substrates, achieved essentially in the past 5 years (late 2018-2023).

Organoantimony Dihydroperoxides: Synthesis, Crystal Structures, and Hydrogen Bonding Networks.

Despite growing interest in the potential applications of p-block hydroperoxo complexes, the chemistry of inorganic hydroperoxides remains largely unexplored. For instance, single-crystal structures of antimony hydroperoxo complexes have not been reported to date. Herein, we present the synthesis of six triaryl and trialkylantimony dihydroperoxides [Me3Sb(OOH)2, Me3Sb(OOH)2·H2O, Ph3Sb(OOH)2·0.75(C4H8O), Ph3Sb(OOH)2·2CH3OH, pTol3Sb(OOH)2, pTol3Sb(OOH)2·2(C4H8O)], obtained by the reaction of the corresponding dibromide antimony(V) complexes with an excess of highly concentrated hydrogen peroxide in the presence of ammonia. The obtained compounds were characterized by single-crystal and powder X-ray diffraction, Fourier transform infrared and Raman spectroscopies, and thermal analysis. The crystal structures of all six compounds reveal hydrogen-bonded networks formed by hydroperoxo ligands. In addition to the previously reported double hydrogen bonding, new types of hydrogen-bonded motifs formed by hydroperoxo ligands were found, including infinite hydroperoxo chains. Solid-state density functional theory calculation of Me3Sb(OOH)2 revealed reasonably strong hydrogen bonding between OOH ligands with an energy of 35 kJ/mol. Additionally, the potential application of Ph3Sb(OOH)2·0.75(C4H8O) as a two-electron oxidant for the enantioselective epoxidation of olefins was investigated in comparison with Ph3SiOOH, Ph3PbOOH, t-BuOOH, and H2O2.

Silver nanoparticle-modified melt-blown polypropylene: Antibacterial and antifungal properties and antiviral activity against SARS-CoV-2.

Melt-blown polymer fiber materials are frequently used in the face mask manufacturing. In the present work, a melt-blown polypropylene tape was modified by silver nanoparticles using chemical metallization. The silver coatings on the fiber surface consisted of crystallites 4-14 nm in size. For the first time, these materials were comprehensively tested for antibacterial, antifungal and antiviral activity. The silver-modified materials showed antibacterial and antifungal activities, especially at high concentrations of silver, and were found to be efficient against the SARS-CoV-2 virus. The silver-modified fiber tape can be used in the face mask manufacturing and as an antimicrobial and antiviral component in filters of liquid and gaseous media.

Electrochemical Behavior of Reduced Graphene Oxide Supported Germanium Oxide, Germanium Nitride, and Germanium Phosphide as Lithium-Ion Battery Anodes Obtained from Highly Soluble Germanium Oxide.

Germanium and germanium-based compounds are widely used in microelectronics, optics, solar cells, and sensors. Recently, germanium and its oxides, nitrides, and phosphides have been studied as active electrode materials in lithium- and sodium-ion battery anodes. Herein, the newly introduced highly soluble germanium oxide (HSGO) was used as a versatile precursor for germanium-based functional materials. In the first stage, a germanium-dioxide-reduced graphene oxide (rGO) composite was obtained by complete precipitation of GeO2 nanoparticles on the GO from an aqueous solution of HSGO and subsequent thermal treatment in argon at low temperature. The composition of the composite, GeO2-rGO (20 to 80 wt.% of crystalline phase), was able to be accurately determined by the HSGO to GO ratio in the initial solution since complete deposition and precipitation were achieved. The chemical activity of germanium dioxide nanoparticles deposited on reduced graphene oxide was shown by conversion to rGO-supported germanium nitride and phosphide phases. The GeP-rGO and Ge3N4-rGO composites with different morphologies were prepared in this study for the first time. As a test case, composite materials with different loadings of GeO2, GeP, and Ge3N4 were evaluated as lithium-ion battery anodes. Reversible conversion-alloying was demonstrated in all cases, and for the low-germanium loading range (20 wt.%), almost theoretical charge capacity based on the germanium content was attained at 100 mA g-1 (i.e., 2595 vs. 2465 mAh g-1 for Ge3N4 and 1790 vs. 1850 mAh g-1 for GeP). The germanium oxide was less efficiently exploited due to its lower conversion reversibility.

Continuous and Discrete Volterra-Laguerre Models With Delay for Modeling of Smooth Pursuit Eye Movements.

The mathematical modeling of the human smooth pursuit system from eye-tracking data is considered. Recently developed algorithms for the estimation of Volterra-Laguerre (VL) models with explicit time delay are applied in continuous and discrete time formulations to experimental data collected from Parkinsonian patients in different medication states and healthy controls. The discrete VL model with an explicit time delay and the method for its estimation are first introduced in this paper. The estimated parameters of a second-order VL model are shown to capture the ocular dynamics both in health and disease. The possibility of including the estimated time delay, along with the VL kernel parameters, into the set of the model parameters is explored. The results obtained in continuous VL modeling are compared with those in discrete time to discern the effects due to the sampling enforced by the eye tracker used for data acquisition.

Speciation of Tellurium(VI) in Aqueous Solutions: Identification of Trinuclear Tellurates by 17O, 123Te, and 125Te NMR Spectroscopy.

Tellurates have attracted the attention of researchers over the past decade due to their properties and as less toxic forms of tellurium derivatives. However, the speciation of Te(VI) in aqueous solutions has not been comprehensively studied. We present a study of the equilibrium speciation of tellurates in aqueous solutions at a wide pH range, 2.5-15 by 17O, 123Te, and 125Te NMR spectroscopy. The coexistence of monomeric, dimeric, and trimeric oxidotellurate species in chemical equilibrium at a wide pH range has been shown. NMR spectroscopy, DFT computations, and single-crystal X-ray diffraction studies confirmed the formation and coexistence of trimeric tellurate anions with linear and triangular structures. Two cesium tellurates, Cs2[Te4O8(OH)10] and Cs2[Te2O4(OH)6], were isolated from the solution at pH 5.5 and 9.2, respectively, and studied by single-crystal X-ray diffractometry, revealing dimeric and tetrameric tellurate anions in corresponding crystal structures.

Impulsive time series modeling with application to luteinizing hormone data.

This work considers the estimation of impulsive time series pertaining to biomedical systems and, in particular, to endocrine ones. We assume a signal model in the form of the output of a continuous linear time-invariant system driven by a sequence of instantaneous impulses, which concept is utilized here, in particular, for modeling of the male reproductive hormone axis. An estimation method to identify the impulsive sequence and the continuous system dynamics from sampled measurements of the output is proposed. Hinging on thorough mathematical analysis, the method improves upon a previously developed least-squares algorithm by resolving the trade-off between model fit and input sparsity, thus removing the need for manual tuning of user-defined estimation algorithm parameters. Experiments with synthetic data and Markov chain Monte-Carlo estimation demonstrate the viability of the proposed method, but also indicate that measurement noise renders the estimation problem ill-posed, as multiple estimates along a curve in the parameter space yield similar fits to data. The method is furthermore applied to clinical luteinizing hormone data collected from healthy males and, for comparability, one female, with similar results. Comparison between the estimated and theoretical elimination rates, as well as simulation of the estimated models, demonstrate the efficacy of the method. The sensitivity of the impulse distribution to the estimated elimination rates is investigated on a subject-specific data subset, revealing that the input sequence and elimination rate estimates can be interdependent. The dose-dependent effect of a selective gonadotropin releasing hormone receptor antagonist on the frequency and weights of the estimated impulses is also analyzed; a significant impact of the medication on the impulse weights is confirmed. To demonstrate the feasibility of the estimation approach for other hormones with pulsatile secretion, the modeling of cortisol data sets collected from three female adolescents was performed.

Fast Quantum Approach for Evaluating the Energy of Non-Covalent Interactions in Molecular Crystals: The Case Study of Intermolecular H-Bonds in Crystalline Peroxosolvates.

Energy/enthalpy of intermolecular hydrogen bonds (H-bonds) in crystals have been calculated in many papers. Most of the theoretical works used non-periodic models. Their applicability for describing intermolecular H-bonds in solids is not obvious since the crystal environment can strongly change H-bond geometry and energy in comparison with non-periodic models. Periodic DFT computations provide a reasonable description of a number of relevant properties of molecular crystals. However, these methods are quite cumbersome and time-consuming compared to non-periodic calculations. Here, we present a fast quantum approach for estimating the energy/enthalpy of intermolecular H-bonds in crystals. It has been tested on a family of crystalline peroxosolvates in which the H∙∙∙O bond set fills evenly (i.e., without significant gaps) the range of H∙∙∙O distances from ~1.5 to ~2.1 Štypical for strong, moderate, and weak H-bonds. Four of these two-component crystals (peroxosolvates of macrocyclic ethers and creatine) were obtained and structurally characterized for the first time. A critical comparison of the approaches for estimating the energy of intermolecular H-bonds in organic crystals is carried out, and various sources of errors are clarified.

Triphenyllead Hydroperoxide: A 1D Coordination Peroxo Polymer, Single-Crystal-to-Single-Crystal Disproportionation to a Superoxo/Hydroxo Complex, and Application in Catalysis.

The synthesis, transformation, and application in catalysis of triphenyllead hydroperoxide, the first dioxygen lead complex, are described. Triphenyllead hydroperoxide is characterized by 207Pb nuclear magnetic resonance (NMR), Fourier transform infrared spectroscopy (FTIR), Raman spectroscopy, and single-crystal X-ray diffraction, revealing the first one-dimensional (1D) coordination peroxo polymer. Photolytic isomorphous transformation of Ph3PbOOH yields a mixed hydroxo/superoxo crystalline structure, the first nonalkali superoxo crystalline metal salt, which is stable up to 100 °C. Upon further photolysis, another isomorphous transformation of the superoxide to hydroxide is observed. These are the first single-crystal-to-single-crystal hydroperoxide-to-superoxide and then to hydroxide transformations reported to date. Photolysis of triphenyllead hydroperoxide yields two forms of superoxide-doped crystalline structures that are distinguished by widely different characteristic relaxation times. The use of Ph3PbOOH as an easy-to-handle solid two-electron oxidant for the highly enantioselective epoxidation of olefins is described.

Comprehensive assessment of NR ligand polypharmacology by a multiplex reporter NR assay.

Nuclear receptors (NR) are ligand-modulated transcription factors that regulate multiple cell functions and thus represent excellent drug targets. However, due to a considerable NR structural homology, NR ligands often interact with multiple receptors. Here, we describe a multiplex reporter assay (the FACTORIAL NR) that enables parallel assessment of NR ligand activity across all 48 human NRs. The assay comprises one-hybrid GAL4-NR reporter modules transiently transfected into test cells. To evaluate the reporter activity, we assessed their RNA transcripts. We used a homogeneous RNA detection approach that afforded equal detection efficacy and permitted the multiplex detection in a single-well format. For validation, we examined a panel of selective NR ligands and polypharmacological agonists and antagonists of the progestin, estrogen, PPAR, ERR, and ROR receptors. The assay produced highly reproducible NR activity profiles (r > 0.96) permitting quantitative assessment of individual NR responses. The inferred EC50 values agreed with the published data. The assay showed excellent quality ( = 0.73) and low variability ( = 7.2%). Furthermore, the assay permitted distinguishing direct and non-direct NR responses to ligands. Therefore, the FACTORIAL NR enables comprehensive evaluation of NR ligand polypharmacology.

Comparison of Proton Acceptor and Proton Donor Properties of H2O and H2O2 in Organic Crystals of Drug-like Compounds: Peroxosolvates vs. Crystallohydrates.

Two new peroxosolvates of drug-like compounds were synthesized and studied by a combination of X-ray crystallographic, Raman spectroscopic methods, and periodic DFT computations. The enthalpies of H-bonds formed by hydrogen peroxide (H2O2) as a donor and an acceptor of protons were compared with the enthalpies of analogous H-bonds formed by water (H2O) in isomorphic (isostructural) hydrates. The enthalpies of H-bonds formed by H2O2 as a proton donor turned out to be higher than the values of the corresponding H-bonds formed by H2O. In the case of H2O2 as a proton acceptor in H-bonds, the ratio appeared reversed. The neutral O∙∙∙H-O/O∙∙∙H-N bonds formed by the lone electron pair of the oxygen atom of water were the strongest H-bonds in the considered crystals. In the paper, it was found out that the low-frequency Raman spectra of isomorphous crystalline hydrate and peroxosolvate of N-(5-Nitro-2-furfurylidene)-1-aminohydantoin are similar. As for the isostructural hydrate and peroxosolvate of the salt of protonated 2-amino-nicotinic acid and maleic acid monoanion, the Raman spectra are different.

A novel chemo-phenotypic method identifies mixtures of salpn, vitamin D3, and pesticides involved in the development of colorectal and pancreatic cancer.

Environmental chemical (EC) exposures and our interactions with them has significantly increased in the recent decades. Toxicity associated biological characterization of these chemicals is challenging and inefficient, even with available high-throughput technologies. In this report, we describe a novel computational method for characterizing toxicity, associated biological perturbations and disease outcome, called the Chemo-Phenotypic Based Toxicity Measurement (CPTM). CPTM is used to quantify the EC "toxicity score" (Zts), which serves as a holistic metric of potential toxicity and disease outcome. CPTM quantitative toxicity is the measure of chemical features, biological phenotypic effects, and toxicokinetic properties of the ECs. For proof-of-concept, we subject ECs obtained from the Environmental Protection Agency's (EPA) database to the CPTM. We validated the CPTM toxicity predictions by correlating 'Zts' scores with known toxicity effects. We also confirmed the CPTM predictions with in-vitro, and in-vivo experiments. In in-vitro and zebrafish models, we showed that, mixtures of the motor oil and food additive 'Salpn' with endogenous nuclear receptor ligands such as Vitamin D3, dysregulated the nuclear receptors and key transcription pathways involved in Colorectal Cancer. Further, in a human patient derived cell organoid model, we found that a mixture of the widely used pesticides 'Tetramethrin' and 'Fenpropathrin' significantly impacts the population of patient derived pancreatic cancer cells and 3D organoid models to support rapid PDAC disease progression. The CPTM method is, to our knowledge, the first comprehensive toxico-physicochemical, and phenotypic bionetwork-based platform for efficient high-throughput screening of environmental chemical toxicity, mechanisms of action, and connection to disease outcomes.

GRAPE: genomic relatedness detection pipeline.

Classifying the degree of relatedness between pairs of individuals has both scientific and commercial applications. As an example, genome-wide association studies (GWAS) may suffer from high rates of false positive results due to unrecognized population structure. This problem becomes especially relevant with recent increases in large-cohort studies. Accurate relationship classification is also required for genetic linkage analysis to identify disease-associated loci. Additionally, DNA relatives matching service is one of the leading drivers for the direct-to-consumer genetic testing market. Despite the availability of scientific and research information on the methods for determining kinship and the accessibility of relevant tools, the assembly of the pipeline, which stably operates on a real-world genotypic data, requires significant research and development resources. Currently, there is no open source end-to-end solution for relatedness detection in genomic data, that is fast, reliable and accurate for both close and distant degrees of kinship, combines all the necessary processing steps to work on a real data, and is ready for production integration. To address this, we developed GRAPE: Genomic RelAtedness detection PipelinE. It combines data preprocessing, identity-by-descent (IBD) segments detection, and accurate relationship estimation. The project uses software development best practices, as well as Global Alliance for Genomics and Health (GA4GH) standards and tools. Pipeline efficiency is demonstrated on both simulated and real-world datasets. GRAPE is available from: https://github.com/genxnetwork/grape.