New access to Alzheimer’s and other neurodegenerative diseases

Single-cell analysis is gaining popularity in the field of mass spectrometry as a method for analyzing protein and peptide content in cells. The spatial resolution of MALDI mass spectrometry (MS) imaging is by a large extent limited by the laser focal diameter and the displacement of analytes during matrix deposition. Owing to recent advancements in both laser optics and matrix deposition methods, spatial resolution on the order of a single eukaryotic cell is now achievable by MALDI MS imaging. Provided adequate instrument sensitivity, a lateral resolution of ?10 µm is currently attainable with commercial instruments. As a result of these advances, MALDI MS imaging is poised to become a transformative clinical technology. In this article, the crucial steps needed to obtain single-cell resolution are discussed, as well as potential applications to disease research.     

Recent advances in single-cell MALDI mass spectrometry imaging and potential clinical impact

Single-cell analysis is gaining popularity in the field of mass spectrometry as a method for analyzing protein and peptide content in cells. The spatial resolution of MALDI mass spectrometry (MS) imaging is by a large extent limited by the laser focal diameter and the displacement of analytes during matrix deposition. Owing to recent advancements in both laser optics and matrix deposition methods, spatial resolution on the order of a single eukaryotic cell is now achievable by MALDI MS imaging. Provided adequate instrument sensitivity, a lateral resolution of approximately 10 μm is currently attainable with commercial instruments. As a result of these advances, MALDI MS imaging is poised to become a transformative clinical technology. In this article, the crucial steps needed to obtain single-cell resolution are discussed, as well as potential applications to disease research.     

Resolution-by-proxy: a simple measure for assessing and comparing the overall quality of NMR protein structures

In protein X-ray crystallography, resolution is often used as a good indicator of structural quality. Diffraction resolution of protein crystals correlates well with the number of X-ray observables that are used in structure generation and, therefore, with protein coordinate errors. In protein NMR, there is no parameter identical to X-ray resolution. Instead, resolution is often used as a synonym of NMR model quality. Resolution of NMR structures is often deduced from ensemble precision, torsion angle normality and number of distance restraints per residue. The lack of common techniques to assess the resolution of X-ray and NMR structures complicates the comparison of structures solved by these two methods. This problem is sometimes approached by calculating "equivalent resolution" from structure quality metrics. However, existing protocols do not offer a comprehensive assessment of protein structure as they calculate equivalent resolution from a relatively small number (<5) of protein parameters. Here, we report a development of a protocol that calculates equivalent resolution from 25 measurable protein features. This new method offers better performance (correlation coefficient of 0.92, mean absolute error of 0.28 ?) than existing predictors of equivalent resolution. Because the method uses coordinate data as a proxy for X-ray diffraction data, we call this measure "Resolution-by-Proxy" or ResProx. We demonstrate that ResProx can be used to identify under-restrained, poorly refined or inaccurate NMR structures, and can discover structural defects that the other equivalent resolution methods cannot detect. The ResProx web server is available at http://www.resprox.ca.     

Two-dimensional standing wave total internal reflection fluorescence microscopy: superresolution imaging of single molecular and biological specimens

The development of high resolution, high speed imaging techniques allows the study of dynamical processes in biological systems. Lateral resolution improvement of up to a factor of 2 has been achieved using structured illumination. In a total internal reflection fluorescence microscope, an evanescence excitation field is formed as light is total internally reflected at an interface between a high and a low index medium. The <100 nm penetration depth of evanescence field ensures a thin excitation region resulting in low background fluorescence. We present even higher resolution wide-field biological imaging by use of standing wave total internal reflection fluorescence (SW-TIRF). Evanescent standing wave (SW) illumination is used to generate a sinusoidal high spatial frequency fringe pattern on specimen for lateral resolution enhancement. To prevent thermal drift of the SW, novel detection and estimation of the SW phase with real-time feedback control is devised for the stabilization and control of the fringe phase. SW-TIRF is a wide-field superresolution technique with resolution better than a fifth of emission wavelength or approximately 100 nm lateral resolution. We demonstrate the performance of the SW-TIRF microscopy using one- and two-directional SW illumination with a biological sample of cellular actin cytoskeleton of mouse fibroblast cells as well as single semiconductor nanocrystal molecules. The results confirm the superior resolution of SW-TIRF in addition to the merit of a high signal/background ratio from TIRF microscopy.     

A Semiquantitative Framework for Gene Regulatory Networks: Increasing the Time and Quantitative Resolution of Boolean Networks

Boolean models have been instrumental in predicting general features of gene networks and more recently also as explorative tools in specific biological applications. In this study we introduce a basic quantitative and a limited time resolution to a discrete (Boolean) framework. Quantitative resolution is improved through the employ of normalized variables in unison with an additive approach. Increased time resolution stems from the introduction of two distinct priority classes. Through the implementation of a previously published chondrocyte network and T helper cell network, we show that this addition of quantitative and time resolution broadens the scope of biological behaviour that can be captured by the models. Specifically, the quantitative resolution readily allows models to discern qualitative differences in dosage response to growth factors. The limited time resolution, in turn, can influence the reachability of attractors, delineating the likely long term system behaviour. Importantly, the information required for implementation of these features, such as the nature of an interaction, is typically obtainable from the literature. Nonetheless, a trade-off is always present between additional computational cost of this approach and the likelihood of extending the model’s scope. Indeed, in some cases the inclusion of these features does not yield additional insight. This framework, incorporating increased and readily available time and semi-quantitative resolution, can help in substantiating the litmus test of dynamics for gene networks, firstly by excluding unlikely dynamics and secondly by refining falsifiable predictions on qualitative behaviour.     

Magnetoacoustic imaging of electrical conductivity of biological tissues at a spatial resolution better than 2 mm

Magnetoacoustic tomography with magnetic induction (MAT-MI) is an emerging approach for noninvasively imaging electrical impedance properties of biological tissues. The MAT-MI imaging system measures ultrasound waves generated by the Lorentz force, having been induced by magnetic stimulation, which is related to the electrical conductivity distribution in tissue samples. MAT-MI promises to provide fine spatial resolution for biological tissue imaging as compared to ultrasound resolution. In the present study, we first estimated the imaging spatial resolution by calculating the full width at half maximum (FWHM) of the system point spread function (PSF). The actual spatial resolution of our MAT-MI system was experimentally determined to be 1.51 mm by a parallel-line-source phantom with Rayleigh criterion. Reconstructed images made from tissue-mimicking gel phantoms, as well as animal tissue samples, were consistent with the morphological structures of the samples. The electrical conductivity value of the samples was determined directly by a calibrated four-electrode system. It has been demonstrated that MAT-MI is able to image the electrical impedance properties of biological tissues with better than 2 mm spatial resolution. These results suggest the potential of MAT-MI for application to early detection of small-size diseased tissues (e.g. small breast cancer).     

Optimum conditions for high-resolution gradient analysis

The effect of experimental variables in the photometric scanning of centrifuged sucrose gradients on the apparent resolution was studied. Better resolution was obtained with a flow cell with a comparatively large diameter flow path that was designed for bulk flow than with a flow cell with a comparatively small diameter flow path that was designed for laminar flow. Degradation of resolution caused by an increase in the flow rate was more apparent with the laminar flow cell than with the bulk flow cell. The resolution increased as the illuminated volume of the flow cell decreased but was relatively insensitive to illuminated volume at the lower values tested. Resolution was determined by the number of pea plyribosomes resolved and the shape of their peaks and by the deterioration in shape of peaks given by zones of southern bean mosaic virus during repetitive scanning. It was found that resolution of ribosomal peaks is not a good quantitative method for characterizing instrumental performance.     

Inverse electrocardiographic transformations: dependence on the number of epicardial regions and body surface data points

The inverse problem of electrocardiography, the computation of epicardial potentials from body surface potentials, is influenced by the desired resolution on the epicardium, the number of recording points on the body surface, and the method of limiting the inversion process. To examine the role of these variables in the computation of the inverse transform, Tikhonov's zero-order regularization and singular value decomposition (SVD) have been used to invert the forward transfer matrix. The inverses have been compared in a data-independent manner using the resolution and the noise amplification as endpoints. Sets of 32, 50, 192, and 384 leads were chosen as sets of body surface data, and 26, 50, 74, and 98 regions were chosen to represent the epicardium.The resolution and noise were both improved by using a greater number of electrodes on the body surface. When 60% of the singular values are retained, the results show a trade-off between noise and resolution, with typical maximal epicardial noise levels of less than 0.5% of maximum epicardial potentials for 26 epicardial regions, 2.5% for 50 epicardial regions, 7.5% for 74 epicardial regions, and 50% for 98 epicardial regions. As the number of epicardial regions is increased, the regularization technique effectively fixes the noise amplification but markedly decreases the resolution, whereas SVD results in an increase in noise and a moderate decrease in resolution. Overall the regularization technique performs slightly better than SVD in the noise-resolution relationship.There is a region at the posterior of the heart that was poorly resolved regardless of the number of regions chosen. The variance of the resolution was such as to suggest the use of variable-size epicardial regions based on the resolution.     

Apoptotic cell-derived metabolites in efferocytosis-mediated resolution of inflammation

The resolution of inflammation, as part of standard host defense mechanism, is the process to guarantee timely termination of inflammatory responses and eventual restoration of tissue homeostasis . It is mainly achieved via efferocytosis, during which pro-resolving macrophages clear apoptotic neutrophils at the inflammatory site. Unfortunately, impaired resolution can be the leading cause of chronic inflammatory disorders and some autoimmune diseases. Existing studies have provided relatively comprehensive understandings about the recognition and uptake of apoptotic neutrophils by macrophages during early phases of efferocytosis. However, lack of information concerns macrophage metabolism of apoptotic cell-derived metabolites after being released from phagolysosomes or the relationship between such metabolism and efferocytosis. Notwithstanding, three recent studies have revealed macrophage metabolism of cholesterol, fatty acids and arginine, as well as their respective functions in the context of inflammation-resolution. This review provides an overview of the resolution of inflammation, efferocytosis and the key players involved, followed by a focus on the metabolism of apoptotic cell-derived metabolites within efferocytes. Hypotheses of more potential apoptotic cell-derived metabolites and their possible roles in the resolution are also formulated. Understanding the effect of these metabolites further advances the concept that apoptotic cells act as active players to regulate resolution, and also suggests novel therapeutic strategies for diseases driven by defective resolution and even cancer that may be treated through enhanced efferocytosis.     

Effects of NMR Spectral Resolution on Protein Structure Calculation

Adequate digital resolution and signal sensitivity are two critical factors for protein structure determinations by solution NMR spectroscopy. The prime objective for obtaining high digital resolution is to resolve peak overlap, especially in NOESY spectra with thousands of signals where the signal analysis needs to be performed on a large scale. Achieving maximum digital resolution is usually limited by the practically available measurement time. We developed a method utilizing non-uniform sampling for balancing digital resolution and signal sensitivity, and performed a large-scale analysis of the effect of the digital resolution on the accuracy of the resulting protein structures. Structure calculations were performed as a function of digital resolution for about 400 proteins with molecular sizes ranging between 5 and 33 kDa. The structural accuracy was assessed by atomic coordinate RMSD values from the reference structures of the proteins. In addition, we monitored also the number of assigned NOESY cross peaks, the average signal sensitivity, and the chemical shift spectral overlap. We show that high resolution is equally important for proteins of every molecular size. The chemical shift spectral overlap depends strongly on the corresponding spectral digital resolution. Thus, knowing the extent of overlap can be a predictor of the resulting structural accuracy. Our results show that for every molecular size a minimal digital resolution, corresponding to the natural linewidth, needs to be achieved for obtaining the highest accuracy possible for the given protein size using state-of-the-art automated NOESY assignment and structure calculation methods.     

Coarse coding: calculation of the resolution achieved by a population of large receptive field neurons

Electrophysiological studies in various sensory systems of different species show that many neurons involved in object localization have large receptive fields. This seems to contradict the high sensory resolution and the behavioral precision observed in localization experiments. Assuming a coarse coding mechanism, the resolution obtained by an ensemble of neurons is analytically calculated as a function of receptive field size. It is shown that particularly large receptive fields yield a high resolution. Received: 7 January 1996 / Accepted in revised form: 7 January 1997     

System of kinetic equations describing large-scale processes in collisionless space plasma

A system of kinetic equations describing relatively slow large-scale processes in collisionless magnetoplasma structures with a spatial resolution of about the characteristic gyroradius is derived. Plasma is assumed to be quasineutral, while the magnetic and electric fields are determined by the instantaneous distributions of the particle and current densities and the stress tensor of all plasma components in the longrange instantaneous interaction approximation. A special version of equations is derived for the case of magnetized electrons described by the Vlasov equation in the drift approximation. The obtained system of equations can be used to develop a global numerical kinetic model of the Earth’s magnetosphere with a spatial resolution of about 100 km, as well as local models of certain regions of the Earth’s magnetosphere with a higher resolution.     

Taxonomic Resolution and Quantification of Freshwater Macroinvertebrate Samples from an Australian Dryland River: The Benefits and Costs of Using Species Abundance Data

In studies using macroinvertebrates as indicators for monitoring rivers and streams, species level identifications in comparison with lower resolution identifications can have greater information content and result in more reliable site classifications and better capacity to discriminate between sites, yet many such programmes identify specimens to the resolution of family rather than species. This is often because it is cheaper to obtain family level data than species level data. Choice of appropriate taxonomic resolution is a compromise between the cost of obtaining data at high taxonomic resolutions and the loss of information at lower resolutions. Optimum taxonomic resolution should be determined by the information required to address programme objectives. Costs saved in identifying macroinvertebrates to family level may not be justified if family level data can not give the answers required and expending the extra cost to obtain species level data may not be warranted if cheaper family level data retains sufficient information to meet objectives. We investigated the influence of taxonomic resolution and sample quantification (abundance vs. presence/absence) on the representation of aquatic macroinvertebrate species assemblage patterns and species richness estimates. The study was conducted in a physically harsh dryland river system (Condamine-Balonne River system, located in south-western Queensland, Australia), characterised by low macroinvertebrate diversity. Our 29 study sites covered a wide geographic range and a diversity of lotic conditions and this was reflected by differences between sites in macroinvertebrate assemblage composition and richness. The usefulness of expending the extra cost necessary to identify macroinvertebrates to species was quantified via the benefits this higher resolution data offered in its capacity to discriminate between sites and give accurate estimates of site species richness. We found that very little information (<6%) was lost by identifying taxa to family (or genus), as opposed to species, and that quantifying the abundance of taxa provided greater resolution for pattern interpretation than simply noting their presence/absence. Species richness was very well represented by genus, family and order richness, so that each of these could be used as surrogates of species richness if, for example, surveying to identify diversity hot-spots. It is suggested that sharing of common ecological responses among species within higher taxonomic units is the most plausible mechanism for the results. Based on a cost/benefit analysis, family level abundance data is recommended as the best resolution for resolving patterns in macroinvertebrate assemblages in this system. The relevance of these findings are discussed in the context of other low diversity, harsh, dryland river systems.     

High resolution scanning electron microscopy of the cell

The scanning electron microscope (SEM) has become a powerful tool for ultrastructural research with improvement of the instrument's resolution and progress in specimen preparation techniques. With regard to resolution, it has been improved step-by-step in this decade and, in 1985, an ultra-high resolution SEM (UHS-T1) was developed, with a resolution of 0.5 nm. Concerning specimen preparation, the osmium-DMSO-osmium method, which is effective for revealing intracellular structures, has come to be widely used. Techniques for observing smaller objects, such as bacteriophages, viruses, and biological macromolecules, have also been devised in recent years. As a result of these preparation techniques and the availability of the ultra-high resolution SEM, the application of SEM in biology is expanding rapidly. In this paper, an outline of the ultra-high resolution SEM, techniques for specimen preparation, findings of some biological materials by these techniques, and guidelines to making the specimens, are described.     

显微CT分辨率对松质骨微观结构及生物力学测量的影响

目的:探究不同分辨率对显微CT测量腰椎松质骨显微结构及显微有限元分析松质骨生物力学参数精确性的影响。方法:以人腰椎L5椎体标本为对象,通过显微CT扫描得到松质骨显微CT数据,扫描分辨率为14μm,通过对合并像素点将分辨率降低至28μm~224μm等,分别测量不同分辨率下,松质骨标本的结构参数;利用不同分辨率下的显微CT数据建立显微有限元模型,计算各正交异性的弹性模量,应用统计学分析比较结构参数和力学参数的在不同分辨率下的差异。结果:各参数与分辨率间相关性不尽相同,BV/TV(骨体积分数)和Tb.Th(平均骨小梁厚度)的数值大小随着分辨率的降低呈增高趋势,Conn.D(骨小梁连接度),BS/BV(骨表面积体积比),Tb.N(平均骨小梁密度)和Tb.Sp(平均骨小梁间距)随着分辨率的降低呈降低趋势。分辨率的改变对SMI(结构模型指数)和DA(骨小梁各向异性度)没有显著影响。在三个轴向上,弹性模量均随着分辨率的降低呈增高趋势,当分辨率大于126μm时,该分辨率下的弹性模量和对照组存在显著性差异(P<0.05)。结论:该实验证实了不同分辨率对显微CT测量腰椎松质骨显微结构和生物力学参数有显著影响。提示在研究腰椎松质骨显微结构和生物力学参数时,采用126μm以上分辨率,可以在不降低准确度的情况下提高运算效率。     

Full field spatially-variant image-based resolution modelling reconstruction for the HRRT

Accurate characterisation of the scanner's point spread function across the entire field of view (FOV) is crucial in order to account for spatially dependent factors that degrade the resolution of the reconstructed images. The HRRT users' community resolution modelling reconstruction software includes a shift-invariant resolution kernel, which leads to transaxially non-uniform resolution in the reconstructed images. Unlike previous work to date in this field, this work is the first to model the spatially variant resolution across the entire FOV of the HRRT, which is the highest resolution human brain PET scanner in the world. In this paper we developed a spatially variant image-based resolution modelling reconstruction dedicated to the HRRT, using an experimentally measured shift-variant resolution kernel. Previously, the system response was measured and characterised in detail across the entire FOV of the HRRT, using a printed point source array. The newly developed resolution modelling reconstruction was applied on measured phantom, as well as clinical data and was compared against the HRRT users' community resolution modelling reconstruction, which is currently in use. Results demonstrated improvements both in contrast and resolution recovery, particularly for regions close to the edges of the FOV, with almost uniform resolution recovery across the entire transverse FOV. In addition, because the newly measured resolution kernel is slightly broader with wider tails, compared to the deliberately conservative kernel employed in the HRRT users' community software, the reconstructed images appear to have not only improved contrast recovery (up to 20% for small regions), but also better noise characteristics.     

A Review of the Deep Learning Methods for Medical Images Super Resolution Problems

Super resolution problems are widely discussed in medical imaging. Spatial resolution of medical images are not sufficient due to the constraints such as image acquisition time, low irradiation dose or hardware limits. To address these problems, different super resolution methods have been proposed, such as optimization or learning-based approaches. Recently, deep learning methods become a thriving technology and are developing at an exponential speed. We think it is necessary to write a review to present the current situation of deep learning in medical imaging super resolution. In this paper, we first briefly introduce deep learning methods, then present a number of important deep learning approaches to solve super resolution problems, different architectures as well as up-sampling operations will be introduced. Afterwards, we focus on the applications of deep learning methods in medical imaging super resolution problems, the challenges to overcome will be presented as well.     

A new approach for structure analysis of two-dimensional membrane protein crystals using X-ray powder diffraction data

The application of powder diffraction methods to problems in structural biology is generally regarded as intractable because of the large number of unresolved, overlapping X‐ray reflections. Here, we use information about unit cell lattice parameters, space group transformations, and chemical composition as a priori information in a bootstrap process that resolves the ambiguities associated with overlapping reflections. The measured ratios of reflections that can be resolved experimentally are used to refine the position, the shape, and the orientation of low‐resolution molecular structures within the unit cell, in leading to the resolution of the overlapping reflections. The molecular model is then made progressively more sophisticated as additional diffraction information is included in the analysis. We apply our method to the recovery of the structure of the bacteriorhodopsin molecule (bR) to a resolution of 7 Å using experimental data obtained from two‐dimensional purple membrane crystals. The approach can be used to determine the structure factors directly or to provide reliable low‐resolution phase information that can be refined further by the conventional methods of protein crystallography.     

A Neurodynamical Model of Visual Attention: Feedback Enhancement of Spatial Resolution in a Hierarchical System

Human beings have the capacity to recognize objects in natural visual scenes with high efficiency despite the complexity of such scenes, which usually contain multiple objects. One possible mechanism for dealing with this problem is selective attention. Psychophysical evidence strongly suggests that selective attention can enhance the spatial resolution in the input region corresponding to the focus of attention. In this work we adopt a computational neuroscience perspective to analyze the attentional enhancement of spatial resolution in the area containing the objects of interest. We extend and apply the computational model of Deco and Schürmann (2000), which consists of several modules with feedforward and feedback interconnections describing the mutual links between different areas of the visual cortex. Each module analyses the visual input with different spatial resolution and can be thought of as a hierarchical predictor at a given level of resolution. Moreover, each hierarchical predictor has a submodule that consists of a group of neurons performing a biologically based 2D Gabor wavelet transformation at a given resolution level. The attention control decides in which local regions the spatial resolution should be enhanced in a serial fashion. In this sense, the scene is first analyzed at a coarse resolution level, and the focus of attention enhances iteratively the resolution at the location of an object until the object is identified. We propose and simulate new psychophysical experiments where the effect of the attentional enhancement of spatial resolution can be demonstrated by predicting different reaction time profiles in visual search experiments where the target and distractors are defined at different levels of resolution.