Different Degrees Of Resolution Research Articles

Exploring multivalent carbohydrate-protein interactions by NMR.

Nuclear Magnetic Resonance (NMR) has been widely employed to assess diverse features of glycan-protein molecular recognition events. Different types of qualitative and quantitative information at different degrees of resolution and complexity can be extracted from the proper application of the available NMR-techniques. In fact, affinity, structural, kinetic, conformational, and dynamic characteristics of the binding process are available. Nevertheless, except in particular cases, the affinity of lectin-sugar interactions is weak, mostly at the low mM range. This feature is overcome in biological processes by using multivalency, thus augmenting the strength of the binding. However, the application of NMR methods to monitor multivalent lectin-glycan interactions is intrinsically challenging. It is well known that when large macromolecular complexes are formed, the NMR signals disappear from the NMR spectrum, due to the existence of fast transverse relaxation, related to the large size and exchange features. Indeed, at the heart of the molecular recognition event, the associated free-bound chemical exchange process for both partners takes place in a particular timescale. Thus, these factors have to be considered and overcome. In this review article, we have distinguished, in a subjective manner, the existence of multivalent presentations in the glycan or in the lectin. From the glycan perspective, we have also considered whether multiple epitopes of a given ligand are presented in the same linear chain of a saccharide (i.e., poly-LacNAc oligosaccharides) or decorating different arms of a multiantennae scaffold, either natural (as in multiantennae N-glycans) or synthetic (of dendrimer or polymer nature). From the lectin perspective, the presence of an individual binding site at every monomer of a multimeric lectin may also have key consequences for the binding event at different levels of complexity.

Omniparticle Contrast Agent for Multimodal Imaging: Synthesis and Characterization in an Animal Model.

Individual imaging modalities have certain advantages, but each suffers from drawbacks that other modalities may overcome. The goal of this study was to create a novel contrast agent suitable for various imaging modalities that after a single administration can bridge and strengthen the collaboration between the research fields as well as enrich the information obtained from any one modality. The contrast agent platform is based on dextran-coated iron oxide nanoparticles (for MRI and MPI) and synthesized using a modified co-precipitation method, followed by a series of conjugation steps with a fluorophore (for fluorescence and photoacoustic imaging), thyroxine (for CT imaging), and chelators for radioisotope labeling (for PET imaging). The fully conjugated agent was then tested in vitro in cell uptake, viability, and phantom studies and in vivo in a model of intraductal injection and in a tumor model. The agent was synthesized, characterized, and tested in vitro where it showed the ability to produce a signal on MRI/MPI/FL/PA/CT and PET images. Studies in cells showed the expected concentration-dependent uptake of the agent without noticeable toxicity. In vivo studies demonstrated localization of the agent to the ductal tree in mice after intraductal injection with different degrees of resolution, with CT being the best for this particular application. In a model of injected labeled tumor cells, the agent produced a signal with all modalities and showed persistence in tumor cells confirmed by histology. A fully functional omniparticle contrast agent was synthesized and tested in vitro and in vivo in two animal models. Results shown here point to the generation of a potent signal in all modalities tested without detrimental toxicity. Future use of this agent includes its exploration in various models of human disease including image-guided diagnostic and therapeutic applications.

Nebulized exosomes derived from allogenic adipose tissue mesenchymal stromal cells in patients with severe COVID-19: a pilot study

BackgroundExisting clinical studies supported the potential efficacy of mesenchymal stromal cells as well as derived exosomes in the treatment of COVID-19. We aimed to explore the safety and efficiency of aerosol inhalation of the exosomes derived from human adipose-derived MSCs (haMSC-Exos) in patients with COVID-19.MethodsThe MEXCOVID trial is a phase 2a single-arm, open-labelled, interventional trial and patients were enrolled in Jinyintan Hospital, Wuhan, China. Eligible 7 patients were assigned to receive the daily dose of haMSCs-Exos (2.0 × 108 nano vesicles) for consecutively 5 days. The primary outcomes included the incidence of prespecified inhalation-associated events and serious adverse events. We also observed the demographic data, clinical characteristics, laboratory results including lymphocyte count, levels of D-dimer and IL-6 as well as chest imaging.ResultsSeven severe COVID-19 related pneumonia patients (4 males and 3 females) were enrolled and received nebulized haMSC-Exos. The median age was 57 year (interquartile range (IQR), 43 year to 70 year). The median time from onset of symptoms to hospital admission and administration of nebulized haMSC-Exos was 30 days (IQR, 15 days to 40 days) and 54 d (IQR, 34 d to 69 d), respectively. All COVID-19 patients tolerated the haMSC-Exos nebulization well, with no evidence of prespecified adverse events or clinical instability during the nebulization or during the immediate post-nebulization period. All patients presented a slight increase of serum lymphocyte counts (median as 1.61 × 109/L vs. 1.78 × 109/L). Different degrees of resolution of pulmonary lesions after aerosol inhalation of haMSC-Exos were observed among all patients, more obviously in 4 of 7 patients.ConclusionsOur trial shows that a consecutive 5 days inhalation dose of clinical grade haMSC-Exos up to a total amount of 2.0 × 109 nano vesicles was feasible and well tolerated in seven COVID-19 patients, with no evidence of prespecified adverse events, immediate clinical instability, or dose-relevant toxicity at any of the doses tested. This safety profile is seemingly followed by CT imaging improvement within 7 days. Further trials will have to confirm the long-term safety or efficacy in larger population.Trial Registration: MEXCOVID, NCT04276987.

Density-Based Clustering of Social Networks

Abstract The idea of the modal formulation of density-based clustering is to associate groups with the regions around the modes of the probability density function underlying the data. The correspondence between clusters and dense regions in the sample space is here exploited to discuss an extension of this approach to the analysis of social networks. Conceptually, the notion of high-density cluster fits well the one of community in a network, regarded to as a collection of individuals with dense local ties in its neighbourhood. The lack of a probabilistic notion of density in networks is turned into a strength of the proposed method, where node-wise measures that quantify the role of actors are used to derive different community configurations. The approach allows for the identification of a hierarchical structure of clusters, which may catch different degrees of resolution of the clustering structure. This feature well fits the nature of social networks, disentangling different involvements of individuals in aggregations.

Partially-averaged Navier–Stokes simulations of turbulent flow past a square cylinder: Comparative assessment of statistics and coherent structures at different resolutions

Scale-resolving simulations of the turbulent wake behind a square cylinder are performed at Re = 22 000 using the partially averaged Navier–Stokes (PANS) k-ω closure model at different degrees of resolution (cut-off scales) corresponding to the unresolved-to-total kinetic energy ratio fk ∈ [0.10, 0.50]. The two principle objectives of the study are to (i) establish the degree of resolution required for an accurate computation of different quantities of interest ranging from flow statistics to coherent structures and (ii) develop a protocol for a quantitative assessment and comparison of the large-scale coherent structures simulated at different degrees of resolution. Straightforward use of proper orthogonal decomposition (POD) to assess and compare large-scale coherence at different resolution levels can prove difficult as small-scale features can affect the POD mode shape and amplitude. To overcome this difficulty, two methods of quantifying coherent structures in the wake are proposed. These methods are based upon the incorporation of Fourier and Chebyshev decompositions with spectral proper orthogonal decomposition, respectively. We examine the first-mode energy spectra and the corresponding streamwise mode shapes using the results generated from PANS simulations at different degrees of resolution. It is demonstrated that increasingly finer resolutions are needed for integral quantities, one-point statistics, frequency spectra, and coherent structures, in that order. The underlying physics is explicated.

Characterization of coherent structures in turbulent wake of a sphere using partially averaged Navier–Stokes (PANS) simulations

The large-scale coherent structures in the wake of a sphere at subcritical Reynolds number (Re = 3700) are examined at different degrees of resolution (filter size) using scale-resolving simulations (SRS) of turbulence. The Partially averaged Navier–Stokes (PANS)-SRS method is employed to compute the wake flow at four levels of resolution marked by unresolved-to-total kinetic energy ratios: fk = 0.5, 0.3, 0.2, 0.1. The results from the four simulations are used to compute one-point statistics, frequency spectra, and spatio-temporal POD (proper orthogonal decomposition) modes. One-point statistics are reasonably well reproduced (in comparison with existing data) at all degrees of resolution. However, the frequency spectra and POD modes exhibit some degree of dependence on the level of resolution. It is demonstrated that accurate depiction of coherent structures is contingent upon adequately resolving key underlying instabilities. The finest resolution PANS simulation (fk = 0.1) is then used to characterize the large-scale coherent structures in the near-wake of the sphere. The main features of this wake, specifically azimuthal mode shapes, modal energy, and frequency content, are compared with experiments and numerical simulations of wakes of other axisymmetric bodies resulting in good agreement. Overall, the study demonstrates that PANS-SRS can capture key one-point statistics and coherent structure features of complex flows in a cost-efficient manner.

Genomics of host-pathogen interactions: challenges and opportunities across ecological and spatiotemporal scales.

Evolutionary genomics has recently entered a new era in the study of host-pathogen interactions. A variety of novel genomic techniques has transformed the identification, detection and classification of both hosts and pathogens, allowing a greater resolution that helps decipher their underlying dynamics and provides novel insights into their environmental context. Nevertheless, many challenges to a general understanding of host-pathogen interactions remain, in particular in the synthesis and integration of concepts and findings across a variety of systems and different spatiotemporal and ecological scales. In this perspective we aim to highlight some of the commonalities and complexities across diverse studies of host-pathogen interactions, with a focus on ecological, spatiotemporal variation, and the choice of genomic methods used. We performed a quantitative review of recent literature to investigate links, patterns and potential tradeoffs between the complexity of genomic, ecological and spatiotemporal scales undertaken in individual host-pathogen studies. We found that the majority of studies used whole genome resolution to address their research objectives across a broad range of ecological scales, especially when focusing on the pathogen side of the interaction. Nevertheless, genomic studies conducted in a complex spatiotemporal context are currently rare in the literature. Because processes of host-pathogen interactions can be understood at multiple scales, from molecular-, cellular-, and physiological-scales to the levels of populations and ecosystems, we conclude that a major obstacle for synthesis across diverse host-pathogen systems is that data are collected on widely diverging scales with different degrees of resolution. This disparity not only hampers effective infrastructural organization of the data but also data granularity and accessibility. Comprehensive metadata deposited in association with genomic data in easily accessible databases will allow greater inference across systems in the future, especially when combined with open data standards and practices. The standardization and comparability of such data will facilitate early detection of emerging infectious diseases as well as studies of the impact of anthropogenic stressors, such as climate change, on disease dynamics in humans and wildlife.

Spin-entanglement wave in a coarse-grained optical lattice

In the present work we explore a suitable coarse graining channel as a tool to describe the effective entanglement spreading in a coarse-grained spin-chain with different degrees of resolution. Comparing it with the experimental realizations performed with ultracold atoms, our results suggest that even if we are not able to fully resolve the system, entanglement can still be detected for some coarse graining levels. Furthermore, we show that it is possible to have some information about the "microscopic" entanglement, even if we have access only to the system's coarse-grained description. We show that the amount of entanglement decays exponentially with the lack of system resolution. The lack of experimental resolution might thus lead to an effective classical description.

Towards an Ecological Trait-data Standard Vocabulary

Trait-based research spans from evolutionary studies of individual-level properties to global patterns of biodiversity and ecosystem functioning. An increasing number of trait data is available for many different organism groups, published as open access data on a variety of file hosting services. Thus, standardization between datasets is generally lacking due to heterogeneous data formats and types. The compilation of these published data into centralised databases remains a difficult and time-consuming task. We reviewed existing trait databases and online services, as well as initiatives for trait data standardization. Together with data providers and users participating in a large long-term observation project on multiple taxa and research questions (the Biodiversity Exploratories, www.biodiversity-exploratories.de), we identified a need for a minimal trait-data terminology that is flexible enough to include traits from all types of organisms but simple enough to be adopted by different research communities. In order to facilitate reproducibility of analyses, the reuse of data and the combination of datasets from multiple sources, we propose a standardized vocabulary for trait data, the Ecological Trait-data Standard Vocabulary (ETS, hosted on GFBio Terminology Service, https://terminologies.gfbio.org/terms/ets/pages), which builds upon and is compatible with existing ontologies. By relying on unambiguous identifiers, the proposed minimal vocabulary for trait data captures the different degrees of resolution and measurement detail for multiple use cases of trait-based research. It further encourages the use of global Uniform Resource Identifiers (URI) for taxa and trait definitions, methods and units, thereby readying the data publication for the semantic web. An accompanying R-package (traitdataform) facilitates the upload of data to hosting services but also simplifies the access to published trait data. While originating from a current need in ecological research, in the next step, the described products are being developed for a seamless fit with broader initiatives on biodiversity data standardisation to foster a better linkage of ecological trait data and global e-infrastructures for biological data. The ETS is maintained and discussion on terms are managed via Github (https://github.com/EcologicalTraitData/ETS).

Seismic and geoelectric modeling studies of parameters controlling CO2 geostorage in saline formations

A possible CO2 geostorage in deep saline formation demands the development of a monitoring strategy using techniques of surface seismic reflection and electrical resistivity tomography (ERT) in boreholes. For this purpose, the resolution and sensitivity of both techniques are studied numerically regarding changes induced by CO2 sequestration.We calculated the effect of partially replacing brine with supercritical CO2 on seismic velocities and densities by using the Gassmann equation. Resulting seismic responses and reflection amplitude changes are quite strong in some cases. For thin CO2 layer (thickness<wavelength) the CO2 anomaly can be delimited laterally quite easier than vertically due to possible reflection overlap from the upper and lower CO2 boundaries.To maximize the ERT resolution, we applied the optimized and tripotential electrode configurations with current flows and potential measurements in different spatial orientations. We performed several comparative 2.5D modelling studies assuming different CO2 saturations, plume scenarios, burial depths, electrode configurations and aspect ratios. The results generally reveal the capability of the techniques to map the storage targets (CO2 plumes, saline host formation and impermeable caprock) with different degrees of resolution, smearing and artefacts. The results show the resolution superiority of the optimized arrays over the other arrays.The highest sensitivity to CO2 saturation changes is found for low saturation case in the seismic and for intermediate and high saturation in the geoelectric case. Therefore, a combination of both methods may be necessary for sn accurate determination of CO2 saturation in situ.A supercritical CO2 plume can be resolved as long as its dimensions are larger than the applied electrode spacing and seismic wavelength, respectively. Thinner layers are problematic, particularly in the ERT technique due to its smearing nature. In the North German Basin strongly the salinity increases strongly with depth, and thus causes a dramatical decrease in the resistivity contrasts and anomalies. The depth effect on the seismic resolution is two-fold: on one hand, the contrast in velocity and density between brine and CO2 increases with depth and enhances the reflection strength accordingly; on the other hand attenuation leads to an increase of wavelength causing a resolution decline.The consideration of seismic results in the inversion of ERT data strongly improves the resolution of the resulting tomograms and the CO2 estimation. It also enables reasonable monitoring (even at aspect ratio<1) of CO2 migrations in large areas and thus reduces the costs of the expensive monitoring wells.

Submitochondrial fragments of brain mitochondria: General characteristics and catalytic properties of NADH:ubiquinone oxidoreductase (Complex I)

A number of genetic or drug-induced pathophysiological disorders, particularly neurodegenerative diseases, have been reported to correlate with catalytic impairments of NADH:ubiquinone oxidoreductase (mitochondrial complex I). The vast majority of the data on catalytic properties of this energy-transducing enzyme have been accumulated from studies on bovine heart complex I preparations of different degrees of resolution, whereas almost nothing is known about the functional activities of the enzyme in neuronal tissues. Here a procedure for preparation of coupled inside-out submitochondrial particles from brain is described and their NADH oxidase activity is characterized. The basic characteristics of brain complex I, particularly the parameters of A/D-transition are found to be essentially the same as those previously reported for heart enzyme. The results show that coupled submitochondrial particles prepared from either heart or brain can equally be used as a model system for in vitro studies aimed to delineate neurodegenerative-associated defects of complex I.

Polyvalent fingerprint based molecular surveillance methods for drinking water supply systems

Despite the relevance for public health, surveillance of drinking water supply systems (DWSS) in Europe is mainly achieved by cultivation based detection of indicator bacteria. The study presented here demonstrates the use of molecular analysis based on fingerprints of DNA extracted from drinking water bacteria as a valuable monitoring tool of DWSS and was exemplified for a DWWS in Northern Germany. The analysis of the bacterial community of drinking water was performed by a set of 16S rRNA gene based fingerprints, sequence analysis of relevant bands and phylogenetic assignment of the 16S rRNA sequences. We assessed the microflora of drinking water originating from two reservoirs in the Harz Mountains. The taxonomic composition of the bacterial communities from both reservoirs was very different at the species level reflecting the different limnological conditions. Detailed analysis of the seasonal community dynamics of the tap water revealed a significant influence of both source waters on the composition of the microflora and demonstrated the relevance of the raw water microflora for the drinking water reaching the consumer. According to our experience, molecular analysis based on fingerprints of different degrees of resolution can be considered as a valuable monitoring tool of DWSS.

Reduced aliasing formulations of the convective terms within the Navier–Stokes equations for a compressible fluid

The effect on aliasing errors of different formulations describing the cubically nonlinear convective terms within the discretized Navier–Stokes equations is examined in the presence of a non-trivial density spectrum. Fourier analysis shows that the existing skew-symmetric forms of the convective term result in reduced aliasing errors relative to the conservation form. Several formulations of the convective term, including a new formulation proposed for cubically nonlinear terms, are tested in direct numerical simulation (DNS) of decaying compressible isotropic turbulence both in chemically inert (small density fluctuations) and reactive cases (large density fluctuations) and for different degrees of resolution. In the DNS of reactive turbulent flow, the new cubic skew-symmetric form gives the most accurate results, consistent with the spectral error analysis, and at the lowest cost. In marginally resolved DNS and LES (poorly resolved by definition) the new cubic skew-symmetric form represents a robust convective formulation which minimizes both aliasing and computational cost while also allowing a reduction in the use of computationally expensive high-order dissipative filters.

Using likelihood ratio functions for modeling the conditional probability of occurrence of future landslides for risk assessment

The most crucial and difficult task in landslide hazard analysis is estimating the conditional probability of occurrence of future landslides in a study area within a specific time period, given specific geomorphic and topographic features. This task can be addressed with a mathematical model that estimates the required conditional probability in two stages: “relative hazard mapping” and “empirical probability estimation.” The first stage divides the study area into a number of “prediction” classes according to their relative likelihood of occurrence of future landslides, based on the geomorphic and topographic data. Each prediction class represents a relative level of hazard with respect to other prediction classes. The number of classes depends on the quantity and quality of input data. Several quantitative models have been developed and tested for use in this stage; the objective is to delineate typical settings in which future landslides are likely to occur. In this stage, problems related to different degrees of resolution in the input data layers are resolved. The second stage is to empirically estimate the conditional probability of landslide occurrence in each prediction class by a cross-validation technique. The basic strategy is to divide past occurrences of landslides into two groups, a “modeling group” and a “validation group”. The first mapping stage is repeated, but the prediction is limited to only those landslide occurrences in the modeling group that are used to construct a new set of prediction classes. The new set of prediction classes is compared to the distribution of landslide occurrences in the validation group. Statistics from the comparison provide a quantitative measure of the conditional probability of occurrence of future landslides.

Development of Methodologies for Different Degrees of Resolution of Linear Alkylbenzene Sulfonates in Groundwater and Wastewater by Liquid Chromatography Using Sodium Dodecyl Sulphate

Linear alkylbenzenesulfonates (LAS) are used extensively as surfactants in consumer formulations as a complex mixture of homologues and isomers. Separation of homologues and isomers of LAS is important in industrial and environmental samples in order to establish their behaviour. Here we present a HPLC methodology with fluorescent detection (FD) for the determination of the homologues and isomers as well as the sum of LAS present. The quantification of total LAS was achieved without a column, using the liquid chromatograph as a FIA system. The different homologues were separated using a Lichrospher-100 RP-8 column of 125 × 4 mm using a linear gradient of methanol and 30.0 mM sodium dodecyl sulphate (SDS), increasing the methanol content linearly from 55% to 70% in 16 min. The resolution of isomers was carried out by using two coupled Lichrospher-100 RP-18 columns of 250 × 4 mm. Elution of isomers was done with a gradient of flow rate from 1.0 to 0.25 mL min−1 using a linear gradient of acetonitrile and 5.0 mM SDS increasing the acetonitrile content linearly from 20% to 40% in 160 min. The methods were validated and applied satisfactorily to the determination of LAS in urban wastewater and ground water.

Retention behaviour of products extracted from oriental medicine formulations in high-performance liquid chromatography on octadecyl acrylate-modified silicas

In this work, octadecyl acrylate (ODA) having a reactive group at one side of the terminal groups were synthesized and evaluated using the extract products in oriental medicine formulations by high-performance liquid chromatography (HPLC). By elemental analysis as well as IR and NMR spectroscopy, the average degree of polymerization of ODA-modified silicas were determined to be 19. Using acetonitrile–water mixtures as the eluent, ginsenosides Rb1 and Rg1 in commercial Panax Ginseng or Red Ginseng were separated on ODA-modified silicas, but with different degrees of resolution comparing with ODS-modified silicas.

Experiments with Reinforcement Learning in Problems with Continuous State and Action Spaces

A key element in the solution of reinforcement learning problems is the value function. The purpose of this function is to measure the long-term utility or value of any given state. The function is important because an agent can use this measure to decide what to do next. A common problem in reinforcement learning when applied to systems having continuous states and action spaces is that the value function must operate with a domain consisting of real-valued variables, which means that it should be able to represent the value of infinitely many state and action pairs. For this reason, function approximators are used to represent the value function when a close-form solution of the optimal policy is not available. In this article, we extend a previously proposed reinforcement learning algorithm so that it can be used with function approximators that generalize the value of individual experiences across both state and action spaces. In particular, we discuss the benefits of using sparse coarse-coded function approximators to represent value functions and describe in detail three implementations: cerebellar model articulation controllers, instance-based, and case-based. Additionally, we discuss how function approximators having different degrees of resolution in different regions of the state and action spaces may influence the performance and learning efficiency of the agent. We propose a simple and modular technique that can be used to implement function approximators with nonuniform degrees of resolution so that the value function can be represented with higher accuracy in important regions of the state and action spaces. We performed extensive experiments in the double-integrator and pendulum swing-up systems to demonstrate the proposed ideas. '

Second Horizontal Derivatives of Ground Magnetic Data Applied to Gold Exploration in thE Yilgarn Craton of Western Australia

Ground magnetic surveys for gold exploration in the Archaean Yilgarn Craton of Western Australia are rapidly being replaced by low-level, high-resolution, fixed-wing and helicopter aeromagnetic surveys for detailed geological mapping of large areas. However, for exploration of areas that are either small, or where the buried magnetic sources are located near the surface, or where the magnetic response of the regolith is of interest, ground magnetic surveys are required in order to measure the high-frequency magnetic responses associated with these environments. Surface and subsurface geological features are often of interest when exploring for near-surface gold mineralisation.Earlier work, by S. Mudge, has shown that bipole plots of second horizontal derivatives of aeromagnetic data are effective in resolving detail in aeromagnetic data. These have been applied to ungridded ground magnetic data and are effective in resolving high-frequency detail in the magnetic responses of subsurface rocks and the regolith. The large high-frequency component of ground magnetic data acquired from maghemite-rich regolith areas presents different and often difficult data processing and presentation problems compared with data acquired from higher-level aeromagnetic surveys. Despite this, second horizontal derivatives of ground magnetic data resolve important detail of magnetic subsurface rocks and the regolith that would otherwise be lost in images and contours of the gridded data.For an area in the Kalgoorlie district of Western Australia, data from a ground magnetic survey and a low-level aeromagnetic survey were transformed with the second horizontal derivative filter to reveal different degrees of resolution of magnetic sources located in the regolith and the subsurface. Line profiles, and images and contours of the gridded data, from both surveys resolved subsurface sources which have assisted with the identification of drill targets. Importantly, however, magnetic features in the regolith were only resolved in the enhanced ground survey data which has assisted with geological mapping of the regolith.

Standard Karyotype of the House Musk Shrew, Suncus murinus (Insectivora, Soricidae).

A high-resolution G-banding technique was used for identification of the chromosomes of the house musk shrew (Suncus murinusu) and for characterizing their individual G-banding pattern. In order to outline the main identifying characteristics of the individual chromosomes and to make comparable the previously published karyotypes of races and individuals, we included in our analysis a detailed study of G-banded chromosomes of different degrees of resolution at metaphase, prometaphase and prophase. On the basis of this study we have constructed idiograms of prometaphase chromosomes and have proposed a standard karyotype of Suncus murinus.

Preparation and evaluation of octadecyl- or phenylpropyl-treated porous glass for the high-performance liquid chromatographic analysis of bufadienolides in Bufonis venenum

The retention and selectivity of bufadienolides (cinobugain, resibufogenin, bufalin) in Bufonis venenum were studied using high-performance liquid chromatography on octadecyl- or phenylpropyl-treated porous glass. From elemental analysis data for carbon, the maximum number of bonded octadecyl or phenylpropyl surface groups per 100 Å 2 of glass (mean pore diameter 157 Å, specific surface area 213 m 2/g) in octadecyl or phenylpropyl gel was calculated to be 2.15 and 1.97, respectively. Using acetonitrile—water mixtures as the eluent, bufadienolides were separated on octadecyl or phenylpropyl gels, but with different degrees of resolution.