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At least 433 records · Page 24Linked to original sources

In-house sulfur SAD phasing: a case study of the effects of data quality and resolution cutoffs.

Single-wavelength anomalous diffraction (SAD) utilizing the weak signal of inherently present S atoms can be successfully used to solve macromolecular structures, although this is mostly performed with data from a synchrotron rather than a laboratory source. Using high redundancy, sufficiently accurate anomalous data may now often be collected in the laboratory using Cu Kalpha X-ray radiation. Systematic analyses of a laboratory-derived data set illuminate the effects of data quality, redundancy and resolution cutoffs on the ability to locate the S atoms and phase the structure of Ptr ToxA, a 13.2 kDa toxin secreted by the fungus Pyrenophora tritici-repentis. Three sulfurs contributed to the successful phasing of the structure and were located using the program SHELXD. It is observed that data quality improves with increasing redundancy, but after a certain point becomes worse owing to crystal decay, so that there is an optimal amount of data to include for the sulfur substructure solution. Further, the success rate in locating S atoms is dramatically improved at lower resolutions and in a manner similar to data quality, there exists an optimal resolution at which the likelihood of solving the substructure is maximized. Based on these observations, a strategy for SAD data collection and substructure solution is suggested.

Crystallization↗

Dynamic tracking of acute ischemic tissue fates using improved unsupervised ISODATA analysis of high-resolution quantitative perfusion and diffusion data.

High-resolution (200 x 200 x 1,500 microm3) imaging was performed to derive quantitative cerebral blood flow (CBF) and apparent diffusion coefficient (ADC) maps in stroke rats (permanent occlusion) every 30 minutes up to 3 hours after occlusion onset, followed by histology at 24 hours. An improved automated iterative-self-organizing-data-analysis-algorithm (ISODATA) was developed to dynamically track ischemic tissue fate on a pixel-by-pixel basis during the acute phase. ISODATA-resolved clusters were overlaid on the CBF-ADC scatterplots and image spaces. Tissue volume ADC, and CBF of each ISODATA cluster were derived. In contrast to the single-cluster normal left hemisphere (ADC = 0.74 +/- 0.02 x 10(-3) mm2/s, CBF = 1.36 +/- 0.22 mL g(-1)min(-1), mean +/- SD, n = 8), the right ischemic hemisphere exhibited three ISODATA clusters, namely: "normal" (normal ADC and CBF), "ischemic core" (low CBF and ADC), and at-risk "perfusion-diffusion mismatch" (low CBF but normal ADC). At 180 minutes, the mismatch disappeared in five rats (Group I, 180-minute "core" lesion volume = 255 +/- 62 mm3 and 24-hour infarct volume = 253 +/- 55 mm3, P > 0.05), while a substantial mismatch persisted in three rats (Group II, 180-minute CBF-abnormal volume = 198 +/- 7 mm3 and 24-hour infarct volume 148 +/- 18 mm3, P < 0.05). The CBF (0.3 +/- 0.09 mL g(-1)min(-1)) of the "persistent mismatch" (Group II, 0.3 +/- 0.09 mL g(-1)min(-1)) was above the CBF viability threshold (0.2 to 0.3 mL g(-1)min(-1)) throughout and its ADC (0.70 +/- 0.03 x 10(-3) mm2/s) did not decrease as ischemia progressed. In contrast, the CBF (0.08 +/- 0.03 mL g(-1)min(-1)) of the analogous brain region in Group I was below the CBF viability threshold, and its ADC gradually decreased from 0.63 +/- 0.05 to 0.43 +/- 0.03 x 10(-3) mm2/s (ADC viability threshold = 0.53 +/- 0.02 x 10(-3) mm2/s). The modified ISODATA analysis of the ADC and CBF tissue characteristics during the acute phase could provide a useful and unbiased means to characterize and predict tissue fates in ischemic brain injury and to monitor therapeutic intervention.

Algorithms↗

Reinvestigation of the use of Patterson maps to extrapolate data to higher resolution.

Many years ago, Karle & Hauptman proposed that the Patterson function could be used for data extrapolation beyond the observed range of the actual measured data. Few people have subsequently attempted to exploit this interesting idea, which might suggest possible limitations of this method, even in structural applications of modest complexity. This appears not to be the case, however, but the original ideas for implementing the extrapolation can be significantly improved. New calculation protocols indicate that Patterson maps may be used to extend observed data sets from 1.0 to approximately 0.5 A resolution with reasonably good precision. Correlation coefficients between the extrapolated F(hkl)'s and their structure-computed expected values typically range between 0.40 and 0.70 across the unobserved range, even for structures containing as many as 600 non-H light atoms in the asymmetric unit. The method is equally good at extrapolating F values for small zones of data that may not have been recorded within the observed resolution range of the diffraction experiment. Furthermore, triplet phase invariants that incorporate one or two extrapolated terms are nearly as reliable as those formed using only the observed data.

Crystallography, X-Ray↗

Possible ancient oceans on Mars: evidence from Mars Orbiter Laser Altimeter data.

High-resolution altimetric data define the detailed topography of the northern lowlands of Mars, and a range of data is consistent with the hypothesis that a lowland-encircling geologic contact represents the ancient shoreline of a large standing body of water present in middle Mars history. The contact altitude is close to an equipotential line, the topography is smoother at all scales below the contact than above it, the volume enclosed by this contact is within the range of estimates of available water on Mars, and a series of extensive terraces parallel the contact in many places.

Evolution, Planetary↗

Image reconstruction: a unifying model for resolution enhancement and data extrapolation. Tutorial.

In reconstructing an object function F(r) from finitely many noisy linear-functional values integral of F(r)Gn(r)dr we face the problem that finite data, noisy or not, are insufficient to specify F(r) uniquely. Estimates based on the finite data may succeed in recovering broad features of F(r), but may fail to resolve important detail. Linear and nonlinear, model-based data extrapolation procedures can be used to improve resolution, but at the cost of sensitivity to noise. To estimate linear-functional values of F(r) that have not been measured from those that have been, we need to employ prior information about the object F(r), such as support information or, more generally, estimates of the overall profile of F(r). One way to do this is through minimum-weighted-norm (MWN) estimation, with the prior information used to determine the weights. The MWN approach extends the Gerchberg-Papoulis band-limited extrapolation method and is closely related to matched-filter linear detection, the approximation of the Wiener filter, and to iterative Shannon-entropy-maximization algorithms. Non-linear versions of the MWN method extend the noniterative, Burg, maximum-entropy spectral-estimation procedure.

Algorithms↗

Impact of the National Practitioner Data Bank on resolution of malpractice claims.

Policymakers and commentators are concerned that the National Practitioner Data Bank (NPDB) has influenced malpractice litigation dynamics. This study examines whether the introduction of the NPDB changed the outcomes, process, and equity of malpractice litigation. Using pre- and post-NPDB analyses, we examine rates of unpaid claims, trials, resolution time, physician defense costs, and payments on claims with a low/high probability of negligence. We find that physicians and their insurers have been less likely to settle claims since introduction of the NPDB, especially for payments less than dollars 50,000. Because this disruption appears to have decreased the proportion of questionable claims receiving compensation, the NPDB actually may have increased overall tort system specificity.

Attitude of Health Personnel↗

Study of protein dynamics by X-ray diffraction.

Properly carried out, high-resolution X-ray diffraction data collection followed by careful least-squares refinement can give the spatial distribution of the high-frequency mean-square displacements in a protein. These displacements reflect both individual atomic fluctuations in hard variables (bond lengths and bond angles) and collective motions involving soft variables (torsion angles, nonbonded interactions). Lower frequency, large amplitude motions and rapid but improbable motions are not quantifiable, but they may lead to such complete disorder that their existence can at least be inferred from the absence of interpretable electron density for some sections of the structure. Interior residues are more rigid than groups on the surface, and structural constraints are reflected in restricted motion even for surface residues. Amplitudes of motion of 0.5 A or greater are not uncommon. The temperature dependence of these fast motions varies considerably over the structure. In general, large [chi 2] values have large temperature dependence, while small displacements are less affected by temperature; however, exceptions are common. Significant reduction in [chi 2] on cooling establishes that proteins are mobile even in the crystalline state, and that static disorder is not the dominant contributor to the individual mean square displacements. Disordered regions in electron density maps are no longer automatically taken as signs of errors in structure determination. It is now recognized that the absence of strong electron density is often an indicator of conformational flexibility. Some of the functional roles for protein dynamics are beginning to be understood. Missing from these results are the physicochemical details that can be extracted from thermal motion analysis of small molecule crystal structures. Application of these methods to protein data is very difficult, but it is well to remember that just over 10 years ago it was commonly felt that protein structures could not even be refined. Certainly some small, well-diffracting proteins should be amenable to many of the sophisticated small-molecule analyses, as they yield X-ray data to resolutions comparable to simple organic structures. The most important type of analysis that awaits is anisotropic B factor refinement, which would give the principal directions of motion added to the amplitude information now obtained. Unfortunately, refinement of unrestrained anisotropic thermal elipsoids requires six parameters for each atom instead of a single isotropic B parameter, and even 1.5 A resolution data do not provide enough overdeterminacy.(ABSTRACT TRUNCATED AT 400 WORDS)

Animals↗

Detection and characterization of metabolites in biological matrices using mass defect filtering of liquid chromatography/high resolution mass spectrometry data.

An improved mass defect filter (MDF) method employing both drug and core structure filter templates was applied to the processing of high resolution liquid chromatography/mass spectrometry (LC/MS) data for the detection and structural characterization of oxidative metabolites with mass defects similar to or significantly different from those of the parent drugs. The effectiveness of this approach was investigated using nefazodone as a model compound, which is known to undergo multiple common and uncommon oxidative reactions. Through the selective removal of all ions that fall outside of the preset filter windows, the MDF process facilitated the detection of all 14 nefazodone metabolites presented in human liver microsomes in the MDF-filtered chromatograms. The capability of the MDF approach to remove endogenous interferences from more complex biological matrices was examined by analyzing omeprazole metabolites in human plasma. The unprocessed mass chromatogram showed no distinct indication of metabolite peaks; however, after MDF processing, the metabolite peaks were easily identified in the chromatogram. Compared with precursor ion scan and neutral loss scan techniques, the MDF approach was shown to be more effective for the detection of metabolites in a complex matrix. The comprehensive metabolite detection capability of the MDF approach, together with accurate mass determination, makes high resolution LC/MS a useful tool for the screening and identification of both common and uncommon drug metabolites.

Biotransformation↗

scBSP: a fast and accurate tool for identifying spatially variable features from high-resolution spatial omics data.

MOTIVATION: Emerging spatial omics technologies empower comprehensive exploration of biological systems from multi-omics perspectives in their native tissue location in 2D and 3D space. However, the limited sequencing depth, increasing spatial resolution, and growing spatial spots in spatial omics technologies present significant computational challenges in identifying biologically meaningful molecules with variable spatial distributions across various omics modalities. RESULTS: We introduce scBSP, an open-source, versatile, and user-friendly package for identifying spatially variable features in large-scale spatial omics data. scBSP demonstrates significantly enhanced computational efficiency, processing high-resolution spatial omics data within seconds, and exhibits robust cross-platform performance by consistently identifying spatially variable features with high reproducibility across various sequencing platforms. AVAILABILITY AND IMPLEMENTATION: scBSP is available for download from R CRAN at https://cran.r-project.org/web/packages/scBSP/index.html and PyPI at https://pypi.org/project/scbsp/.

Software↗

Virtual endoscopy of the tympanic cavity based on high-resolution multislice computed tomographic data.

OBJECTIVE: This study was designed to assess the value of high-resolution multislice computed tomography (MSCT) data of the petrous bone for the virtual endoscopic visualization of the tympanic cavity. BACKGROUND: The recently introduced MSCT technology has improved spatial resolution in the z axis as well as scan speed in computed tomography. Three-dimensional rendering of high-resolution MSCT data of the petrous bone may be expected to provide endoluminal views of superior image quality, thus competing with transtympanic endoscopy (otoendoscopy). SETTING: This study was conducted at a university teaching hospital. MATERIALS AND METHODS: Cadaveric phantom studies in a MSCT scanner were performed to define a data acquisition protocol, combining adequate detail resolution with low tube current. Subsequently, the cadaveric phantom underwent otoendoscopy. The postprocessing parameters of the three-dimensional rendering protocol were chosen to produce views closely resembling the corresponding otoendoscopic images. High-resolution data from 18 patients with pathologic conditions of the middle ear, as suggested by clinical findings and assessment of cross-sectional data, were postprocessed using the volume rendering technique to generate standardized virtual endoscopic views. A total of 36 virtual endoscopic scans of the tympanic cavity were generated. RESULTS: With regard to intermediate and high-density structures, virtual endoscopic images, based on MSCT data, yielded endoluminal views closely resembling corresponding otoendoscopic views. Virtual endoscopy seems useful for imaging ossicular pathologic conditions such as dysplasia and chain disruption as well as for assessing patient status before and after otosurgery. CONCLUSION: MSCT data sets allow for generating virtual endoscopic views closely resembling otoendoscopic images. The technique is especially useful when ossicular pathologic changes are present as well as for preoperative and postoperative imaging of otologic procedures.

Endoscopy↗

Bayesian neural network approaches to ovarian cancer identification from high-resolution mass spectrometry data.

MOTIVATION: The classification of high-dimensional data is always a challenge to statistical machine learning. We propose a novel method named shallow feature selection that assigns each feature a probability of being selected based on the structure of training data itself. Independent of particular classifiers, the high dimension of biodata can be fleetly reduced to an applicable case for consequential processing. Moreover, to improve both efficiency and performance of classification, these prior probabilities are further used to specify the distributions of top-level hyperparameters in hierarchical models of Bayesian neural network (BNN), as well as the parameters in Gaussian process models. RESULTS: Three BNN approaches were derived and then applied to identify ovarian cancer from NCI's high-resolution mass spectrometry data, which yielded an excellent performance in 1000 independent k-fold cross validations (k = 2,...,10). For instance, indices of average sensitivity and specificity of 98.56 and 98.42%, respectively, were achieved in the 2-fold cross validations. Furthermore, only one control and one cancer were misclassified in the leave-one-out cross validation. Some other popular classifiers were also tested for comparison. AVAILABILITY: The programs implemented in MatLab, R and Neal's fbm.2004-11-10.

Bayes Theorem↗

The use of ACORN in solving a 39.5 kDa macromolecule with 1.9 A resolution laboratory source data.

Data from the alkaline cellulase apo form were collected at a resolution of 1.9 A using an in-house X-ray source (Cu K alpha). By using different fragments of helices from the model solved by macromolecular crystallographic means, the direct-methods program ACORN was used to arrive at the complete model. Attempts have been made to use various percentages of input phasing information from these helices. The minimum input phasing required in feeding the fragments was about 14% of the whole structure. The phases obtained from ACORN were of superb quality, allowing automated model building to be carried out using ARP/wARP. Minimal manual model building was required and the structure determination was completed using the maximum-likelihood refinement program REFMAC. The whole process, starting from the running of ACORN and ending with the refined model, took nearly 15 h of CPU time using a Pentium III PC.

Algorithms↗

Determination of volatile components in ginger using gas chromatography-mass spectrometry with resolution improved by data processing techniques.

Ginger is widely used as either a food product or an herbal medicine in the world. In this paper, a method was developed for determining volatile components in essential oils from both dried and fresh ginger by use of gas chromatography-mass spectrometry (GC-MS) and chemometric approaches. With the resolution improvement by chemometric methods upon two-dimensional data from GC-MS, the drifting baseline can be corrected. In addition, the peak purity can be assessed and the number of chemical components and their stepwise elution in the peak clusters can be identified. The peak clusters investigated are then resolved into pure chromatograms and related mass spectra for each of the components involved. Finally, with the pure chromatograms and related mass spectra obtained, the chemical components can be qualitatively identified based on the similarity searches in the MS databases and the chromatographic retention times. Quantitative determination can be conducted using the overall volume integration approach. The results showed that 140 and 136 components were separated and that 74 and 75 of them were tentatively identified, which accounted for about 62.82 and 47.11% of the total relative content for dried and fresh ginger, respectively. In comparison with the chromatographic fingerprints of essential oils from dried and fresh ginger, 60 of the volatile components determined match with each other. The study demonstrated that the use of chemometric resolution based on two-dimensional data can mathematically enhance the separation ability of GC-MS and assist qualitative and quantitative determination of chemical components separated from complicated practical systems such as foods, herbal medicines, and environmental samples.

Food Preservation↗

Application of multivariate curve resolution to voltammetric data. II. Study of metal-binding properties of the peptides.

The complexation of Cd2+ by glutathione (GSH), in 0.13 m borate buffer at pH 9.5, was studied by differential pulse polarography (DPP) and multivariate curve resolution. The Cd-GSH system has been chosen as a model to check the possibilities of this new polarographic approach to the study of metal ion complexation by peptides. Experimental data obtained by DPP for different Cd2+-to-GSH concentration ratios have been analyzed by a procedure which consists of using several chemometrical techniques based on factor analysis: principal component analysis, evolving factor analysis, and multivariate curve resolution with alternating least-squares (ALS) optimization. The use of different constraints during the ALS optimization process, such as nonnegativity and unimodality constraints, yields the optimal sought solution from a chemical point of view. In the present work, a new constraint has been implemented during ALS optimization to take into account the expected peak-shaped signal of DPP. This data treatment allows us to detect simultaneously the formation of 1:1 and 1:2 Cd:GSH complexes which were very difficult to detect by univariate analysis of DPP data. It is concluded that the described multivariate curve resolution method could be a reliable tool for studying metal-binding properties of peptides.

Cadmium↗

MASSFORM: a computer program for the assignment of elemental compositions to high resolution mass spectral data.

This paper describes a computer program which calculates all possible empirical formulas for each accurately measured mass in a high resolution mass spectrum. The program, MASSFORM, incorporates a novel mechanism for classifying the empirical formulas generated according to their empirical formula. This mechanism makes it possible to use a set of general empirical formulas to aid in the analysis of complex mixtures in much less time than most other such programs. The program is being used as an important aid to environmental studies.

Chemical Phenomena↗

CT volumetry of the skeletal tissues.

Computed tomography (CT) is an important and widely used modality in the diagnosis and treatment of various cancers. In the field of molecular radiotherapy, the use of spongiosa volume (combined tissues of the bone marrow and bone trabeculae) has been suggested as a means to improve the patient-specificity of bone marrow dose estimates. The noninvasive estimation of an organ volume comes with some degree of error or variation from the true organ volume. The present study explores the ability to obtain estimates of spongiosa volume or its surrogate via manual image segmentation. The variation among different segmentation raters was explored and found not to be statistically significant (p value >0.05). Accuracy was assessed by having several raters manually segment a polyvinyl chloride (PVC) pipe with known volumes. Segmentation of the outer region of the PVC pipe resulted in mean percent errors as great as 15% while segmentation of the pipe's inner region resulted in mean percent errors within approximately 5%. Differences between volumes estimated with the high-resolution CT data set (typical of ex vivo skeletal scans) and the low-resolution CT data set (typical of in vivo skeletal scans) were also explored using both patient CT images and a PVC pipe phantom. While a statistically significant difference (p value <0.002) between the high-resolution and low-resolution data sets was observed with excised femoral heads obtained following total hip arthroplasty, the mean difference between high-resolution and low-resolution data sets was found to be only 1.24 and 2.18 cm3 for spongiosa and cortical bone, respectively. With respect to differences observed with the PVC pipe, the variation between the high-resolution and low-resolution mean percent errors was a high as approximately 20% for the outer region volume estimates and only as high as approximately 6% for the inner region volume estimates. The findings from this study suggest that manual segmentation is a reasonably accurate and reliable means for the in vivo estimation of spongiosa volume. This work also provides a foundation for future studies where spongiosa volumes are estimated by various raters in more comprehensive CT data

Anatomy, Cross-Sectional↗

The invariom model and its application: refinement of D,L-serine at different temperatures and resolution.

Three X-ray data sets of the same D,L-serine crystal were measured at temperatures of 298, 100 and 20 K. These data were then evaluated using invarioms and the Hansen & Coppens aspherical-atom model. Multipole populations for invarioms, which are pseudoatoms that remain approximately invariant in an intermolecular transfer, were theoretically predicted using different density functional theorem (DFT) basis sets. The invariom parameters were kept fixed and positional and thermal parameters were refined to compare the fitting against the multi-temperature data at different resolutions. The deconvolution of thermal motion and electron density with respect to data resolution was studied by application of the Hirshfeld test. Above a resolution of sin theta/lambda approximately 0.55 A-1, or d approximately 0.9 A, this test was fulfilled. When the Hirshfeld test is fulfilled, a successful modeling of the aspherical electron density with invarioms is achieved, which was proven by Fourier methods. Molecular geometry improves, especially for H atoms, when using the invariom method compared to the independent-atom model, as a comparison with neutron data shows. Based on this example, the general applicability of the invariom concept to organic molecules is proven and the aspherical density modeling of a larger biomacromolecule is within reach.

Crystallography, X-Ray↗

Three-dimensional reconstructions from incomplete data: interpretability of density maps at "atomic" resolution.

Three dimensional data collection in electron microscopy is normally limited to a range of tilt angles that is less than +/- 90 degrees. Thus, even under the best conditions, experimental values of the structure factors will be missing within a solid cone in reciprocal space. Previous work has already shown that the missing cone of data can produce serious artifacts in three-dimensional density maps at modest resolution, for example approximately 15A. We now report, however, that a missing cone as large as +/- 30 degrees appears to have no serious effect on the three-dimensional density map of a protein at 3.6 A resolution, and we attribute this result to the fact that the electron density features are quite well separated from one another at that resolution. The map calculated with a +/- 30 degree missing cone is, furthermore, no more sensitive to noise (error) than is the full (isotropic) Fourier map. This result does not seem to be unreasonable in view of the fact that less than 14% of the data (i.e., signal) is lost due to the missing cone. Our numerical simulations therefore indicate that there should be no difficulty in interpreting high-resolution Fourier maps that can be produced with data that fall within realistic estimates of achievable resolution, tilt angles, and experimental error.

Electronic Data Processing↗