Computational Evaluation of Abrogation of HBx-Bcl-xL Complex with High-Affinity Carbon Nanotubes (Fullerene) to Halt the Hepatitis B Virus Replication

Hepatitis B virus (HBV) is the world's most prevalent chronic viral infection. More than 350 million individuals are chronic carriers of the virus, with an estimated 2 billion infected persons. For instance, the role of HBx protein in attachment and infection is very obvious and consequently deemed as an important druggable target. Targeting the interface and discovering novel drugs greatly advanced the field of therapeutics development. Therefore, in the current study, HBx to Bcl-xL is abrogated on high-affinity carbon nanotubes using computational structural biology tools. Our analysis revealed that among the total 62 carbon fullerenes, only 13 compounds exhibited inhibitory activity against HBx, which was further confirmed through IFD-based rescoring. Structural dynamics investigation revealed stable binding, compactness, and hydrogen bonds reprogramming. Moreover, the binding free energy calculation results revealed that the top hits1-4 possess the total binding energy of -54.36 kcal/mol (hit1), -50.81 kcal/mol (hit2), -47.09 kcal/mol (hit3), and -45.59 kcal/mol for hit4. In addition, the predicted KD values and bioactivity scores further validated the inhibitory potential of these top hits. The identified compounds need further in vitro and in vivo validation to aid the treatment process of HBV.

A Supramolecular Antidote to Macromolecular Toxins Prepared through Coassembly of Macrocyclic Amphiphiles

Poisoning is a leading cause of admission to medical emergency departments and intensive care units. Supramolecular detoxification, which involves injecting supramolecular receptors that bind with toxins to suppress their biological activity, is an emerging strategy for poisoning treatment; it has few requirements and a broad application scope. However, it is still a formidable challenge to design supramolecular therapeutic materials as an antidote to macromolecular toxins, because the large size, flexible conformation, and presence of multiple and diverse binding sites of biomacromolecules hinder their recognition. Herein, a supramolecular antidote to macromolecular toxins is developed through the coassembly of macrocyclic amphiphiles, relying on heteromultivalent recognition between the coassembled components and toxic macromolecules. The coassembly of amphiphilic cyclodextrin and calixarene strongly and selectively captures melittin, a toxin studied herein; this imparts various therapeutic effects such as inhibiting the interactions of melittin with cell membranes, alleviating melittin cytotoxicity and hemolytic toxicity, reducing the mortality rate of melittin-poisoned mice, and mitigating damage to major organs. The use of the proposed antidote overcomes the limitation of supramolecular detoxification applicability to only small-molecular toxins. The antidote can also detoxify other macromolecular toxins as long as selective and strong binding is achieved because of the coassembling tunability.

Genesis of Neurotoxic Hybrid Nanofibers from the Coassembly of Aromatic Amino Acids

Considering the relevance of accumulation and self-assembly of metabolites and aftermath of biological consequences, it is important to know whether they undergo coassembly and what properties the resultant hybrid higher-order structures would exhibit. This work reveals the inherent tendency of aromatic amino acids to undergo a spontaneous coassembly process under physiologically mimicked conditions, which yields neurotoxic hybrid nanofibers. Resultant hybrid nanostructures resembled the β-structured conformers stabilized by H-bonds and π-π stacking interactions, which were highly toxic to human neuroblastoma cells. The hybrid nanofibers also showed strong cross-seeding potential that triggered in vitro aggregation of diverse globular proteins and brain extract components, converting the native structures into cross-β-rich amyloid aggregates. The heterogenic nature of the hybrid nanofibers seems crucial for their higher toxicity and faster cross-seeding potential as compared to the homogeneous amino acid nanofibers. Our findings reveal the importance of aromaticity-driven optimized intermolecular arrangements for the coassembly of aromatic amino acids, and the results may provide important clues to the fundamental understanding of metabolite accumulation-related complications.

Supramolecular Cylinders Target Bulge Structures in the 5' UTR of the RNA Genome of SARS-CoV-2 and Inhibit Viral Replication*

The untranslated regions (UTRs) of viral genomes contain a variety of conserved yet dynamic structures crucial for viral replication, providing drug targets for the development of broad spectrum anti-virals. We combine in vitro RNA analysis with molecular dynamics simulations to build the first 3D models of the structure and dynamics of key regions of the 5' UTR of the SARS-CoV-2 genome. Furthermore, we determine the binding of metallo-supramolecular helicates (cylinders) to this RNA structure. These nano-size agents are uniquely able to thread through RNA junctions and we identify their binding to a 3-base bulge and the central cross 4-way junction located in stem loop 5. Finally, we show these RNA-binding cylinders suppress SARS-CoV-2 replication, highlighting their potential as novel anti-viral agents.

A beginner's guideline for low-cost 3D printing of macromolecules usable for teaching and demonstration

The structure and function of biomolecules relationship is the hallmark of biochemistry, molecular biology, and life sciences in general. Physical models of macromolecules give students the possibility to manipulate these structures in three dimensions, developing a sense of spatiality and a better understanding of key aspects such as atom size and shape, bond lengths and symmetry. Several molecular model systems were developed specifically to represent particular classes or groups of molecules and hence lack the flexibility of a universal solution. Three-dimensional printing could nevertheless provide such a universal solution, as it can be used to create physical models of biomolecular structures based on the teacher's or demonstrator's needs and requirements. Here, insulin was used as a model molecule and several depiction and printing parameters were tested in order to highlight the technical limitations of the approach. In the end, a set of settings that worked is provided which could serve as a starting point for anyone wishing to print his or her own custom macromolecular model on the cheap.

Intra-vessel heterogeneity establishes enhanced sites of macromolecular leakage downstream of laminin α5

Endothelial cells display heterogeneous properties based on location and function. How this heterogeneity influences endothelial barrier stability both between and within vessel subtypes is unexplored. In this study, we find that endothelial cells exhibit heterogeneous barrier properties on inter-organ and intra-vessel levels. Using intravital microscopy and sequential stimulation of the ear dermis with vascular endothelial growth factor-A (VEGFA) and/or histamine, we observe distinct, reappearing sites, common for both agonists, where leakage preferentially takes place. Through repetitive stimulation of the diaphragm and trachea, we find inter-organ conservation of such predetermined leakage sites. Qualitatively, predetermined sites display distinct leakage properties and enhanced barrier breakdown compared to less susceptible regions. Mechanistically, laminin α5 is reduced at predetermined sites, which is linked to reduced junctional vascular endothelial (VE)-cadherin and enhanced VEGFA-induced VE-cadherin phosphorylation. These data highlight functional intra-vessel heterogeneity that defines predetermined sites with distinct leakage properties and that may disproportionately impact pathological vascular leakage.

Synapsin Condensates Recruit alpha-Synuclein

Neurotransmission relies on the tight spatial and temporal regulation of the synaptic vesicle (SV) cycle. Nerve terminals contain hundreds of SVs that form tight clusters. These clusters represent a distinct liquid phase in which one component of the phase are SVs and the other synapsin 1, a highly abundant synaptic protein. Another major family of disordered proteins at the presynapse includes synucleins, most notably α-synuclein. The precise physiological role of α-synuclein in synaptic physiology remains elusive, albeit its role has been implicated in nearly all steps of the SV cycle. To determine the effect of α-synuclein on the synapsin phase, we employ the reconstitution approach using natively purified SVs from rat brains and the heterologous cell system to generate synapsin condensates. We demonstrate that synapsin condensates recruit α-synuclein, and while enriched into these synapsin condensates, α-synuclein still maintains its high mobility. The presence of SVs enhances the rate of synapsin/α-synuclein condensation, suggesting that SVs act as catalyzers for the formation of synapsin condensates. Notably, at physiological salt and protein concentrations, α-synuclein alone is not able to cluster isolated SVs. Excess of α-synuclein disrupts the kinetics of synapsin/SV condensate formation, indicating that the molar ratio between synapsin and α-synuclein is important in assembling the functional condensates of SVs. Understanding the molecular mechanism of α-synuclein interactions at the nerve terminals is crucial for clarifying the pathogenesis of synucleinopathies, where α-synuclein, synaptic proteins and lipid organelles all accumulate as insoluble intracellular inclusions.

Contribution of macromolecules to brain 1 H MR spectra: Experts' consensus recommendations

Proton MR spectra of the brain, especially those measured at short and intermediate echo times, contain signals from mobile macromolecules (MM). A description of the main MM is provided in this consensus paper. These broad peaks of MM underlie the narrower peaks of metabolites and often complicate their quantification but they also may have potential importance as biomarkers in specific diseases. Thus, separation of broad MM signals from low molecular weight metabolites enables accurate determination of metabolite concentrations and is of primary interest in many studies. Other studies attempt to understand the origin of the MM spectrum, to decompose it into individual spectral regions or peaks and to use the components of the MM spectrum as markers of various physiological or pathological conditions in biomedical research or clinical practice. The aim of this consensus paper is to provide an overview and some recommendations on how to handle the MM signals in different types of studies together with a list of open issues in the field, which are all summarized at the end of the paper.

Longitudinal quantification of metabolites and macromolecules reveals age- and sex-related changes in the healthy Fischer 344 rat brain

Normal aging is associated with numerous biological changes, including altered brain metabolism and tissue chemistry. In vivo characterization of the neurochemical profile during aging is possible using magnetic resonance spectroscopy, a powerful noninvasive technique capable of quantifying brain metabolites involved in physiological processes that become impaired with age. A prominent macromolecular signal underlies those of brain metabolites and is particularly visible at high fields; parameterization of this signal into components improves quantification and expands the number of biomarkers comprising the neurochemical profile. The present study reports, for the first time, the simultaneous absolute quantification of brain metabolites and individual macromolecules in aging male and female Fischer 344 rats, measured longitudinally using proton magnetic resonance spectroscopy at 7 T. We identified age- and sex-related changes in neurochemistry, with prominent differences in metabolites implicated in anaerobic energy metabolism, antioxidant defenses, and neuroprotection, as well as numerous macromolecule changes. These findings contribute to our understanding of the neurobiological processes associated with healthy aging, critical for the proper identification and management of pathologic aging trajectories. This article is part of the Virtual Special Issue titled COGNITIVE NEUROSCIENCE OF HEALTHY AND PATHOLOGICAL AGING. The full issue can be found on ScienceDirect athttps://www.sciencedirect.com/journal/neurobiology-of-aging/special-issue/105379XPWJP.

Influence of fitting approaches in LCModel on MRS quantification focusing on age-specific macromolecules and the spline baseline

Quantification of neurochemical concentrations from ¹ H MR spectra is challenged by incomplete knowledge of contributing signals. Some experimental conditions hinder the acquisition of artifact-free spectra and impede the acquisition of condition-specific macromolecule (MM) spectra. This work studies differences caused by fitting solutions routinely employed to manage resonances from MM and lipids. High quality spectra (free of residual water and lipid artifacts and for which condition-specific MM spectra are available) are used to understand the influences of spline baseline flexibility and noncondition-specific MM on neurochemical quantification. Fitting with moderate spline flexibility or using noncondition-specific MM led to quantification that differed from when an appropriate, fully specified model was used. This occurred for all neurochemicals to an extent that varied in magnitude among and within approaches. The spline baseline was more tortuous when less constrained and when used in combination with noncondition-specific MM. Increasing baseline flexibility did not reproduce concentrations quantified under appropriate conditions when spectra were fitted using a MM spectrum measured from a mismatched cohort. Using the noncondition-specific MM spectrum led to quantification differences that were comparable in size with using a fitting model that had moderate freedom, and these influences were additive. Although goodness of fit was better with greater fitting flexibility, quantification differed from when fitting with a fully specified model that is appropriate for low noise data. Notable GABA and PE concentration differences occurred with lower estimates of measurement error when fitting with greater spline flexibility or noncondition-specific MM. These data support the need for improved metrics of goodness of fit. Attempting to correct for artifacts or absence of a condition-specific MM spectrum via increased spline flexibility and usage of noncondition-specific MM spectra cannot replace artifact-free data quantified with a condition-specific MM spectrum.

Hyaluronic Acid as Macromolecular Crowder in Equine Adipose-Derived Stem Cell Cultures

The use of macromolecular crowding in the development of extracellular matrix-rich cell-assembled tissue equivalents is continuously gaining pace in regenerative engineering. Despite the significant advancements in the field, the optimal macromolecular crowder still remains elusive. Herein, the physicochemical properties of different concentrations of different molecular weights hyaluronic acid (HA) and their influence on equine adipose-derived stem cell cultures were assessed. Within the different concentrations and molecular weight HAs, the 10 mg/mL 100 kDa and 500 kDa HAs exhibited the highest negative charge and hydrodynamic radius, and the 10 mg/mL 100 kDa HA exhibited the lowest polydispersity index and the highest % fraction volume occupancy. Although HA had the potential to act as a macromolecular crowding agent, it did not outperform carrageenan and Ficoll®, the most widely used macromolecular crowding molecules, in enhanced and accelerated collagen I, collagen III and collagen IV deposition.

Nanoparticle-Assembled Vacuolated Coacervates Control Macromolecule Spatiotemporal Distribution to Provide a Stable Segregated Cell Microenvironment

Membraneless coacervate compartments in the intracellular and pericellular space mediate critical cellular functions. Developing synthetic coacervates that emulate the morphological, physical, and functional complexity of these natural coacervates is challenging but highly desirable. Herein, a generalizable nanoparticle assembly (NPA) strategy is developed, which is applicable to interactive core-shell nanoparticles with different chemical makeups, to fabricate vacuolated coacervates. The obtained NPA coacervates contain stable internal vacuoles to provide segregated microcompartments, which can mediate the spatially heterogeneous distribution of diverse macromolecules via restricted diffusion. It is further shown that the vacuolated NPA coacervates can harbor and retain macromolecular medium supplements to regulate the functions of cells encapsulated in vacuoles. Furthermore, the restricted macromolecule diffusion can be abolished on demand via the triggered coacervate-hydrogel transition, thereby altering the exposure of encapsulated cells to environmental factors. It is believed that the NPA strategy provides new insights into the design principles of hierarchical coacervates that hold promising potential for a wide array of biomedical applications.

RNA contributions to the form and function of biomolecular condensates

Biomolecular condensation partitions cellular contents and has important roles in stress responses, maintaining homeostasis, development and disease. Many nuclear and cytoplasmic condensates are rich in RNA and RNA-binding proteins (RBPs), which undergo liquid-liquid phase separation (LLPS). Whereas the role of RBPs in condensates has been well studied, less attention has been paid to the contribution of RNA to LLPS. In this Review, we discuss the role of RNA in biomolecular condensation and highlight considerations for designing condensate reconstitution experiments. We focus on RNA properties such as composition, length, structure, modifications and expression level. These properties can modulate the biophysical features of native condensates, including their size, shape, viscosity, liquidity, surface tension and composition. We also discuss the role of RNA-protein condensates in development, disease and homeostasis, emphasizing how their properties and function can be determined by RNA. Finally, we discuss the multifaceted cellular functions of biomolecular condensates, including cell compartmentalization through RNA transport and localization, supporting catalytic processes, storage and inheritance of specific molecules, and buffering noise and responding to stress.

Supramolecular Bait to Trigger Non-Equilibrium Co-Assembly and Clearance of Aβ42

In living systems, non-equilibrium states that control the assembly-disassembly of cellular components underlie the gradual complexification of life, whereas in nonliving systems, most molecules follow the laws of thermodynamic equilibrium to sustain dynamic consistency. Little is known about the roles of non-equilibrium states of interactions between supramolecules in living systems. Here, a non-equilibrium state of interaction between supramolecular lipopolysaccharide (LPS) and Aβ42, an aggregate-prone protein that causes Alzheimer's disease (AD), was identified. Structurally, Aβ42 presents a specific groove that is recognized by the amphiphilicity of LPS bait in a non-equilibrium manner. Functionally, the transient complex elicits a cellular response to clear extracellular Aβ42 deposits in neuronal cells. Since the impaired clearance of toxic Aβ42 deposits correlates with AD pathology, the non-equilibrium LPS and Aβ42 could represent a useful target for developing AD therapeutics.

An Appraisal of Computer Simulation Approaches in Elucidating Biomolecular Recognition Pathways

Computer simulation approaches in biomolecular recognition processes have come a long way. In this Perspective, we highlight a series of recent success stories in which computer simulations have played a remarkable role in elucidating the atomic resolution mechanism of kinetic processes of protein-ligand binding in a quantitative fashion. In particular, we show that a robust combination of unbiased simulation, harnessed by a high-fidelity computing environment, and Markov state modeling approaches has been instrumental in revealing novel protein-ligand recognition pathways in multiple systems. We also elucidate the role of recent developments in enhanced sampling approaches in providing the much-needed impetus in accelerating simulation of the ligand recognition process. We identify multiple key issues, including force fields and the sampling bottleneck, which are currently preventing the field from achieving quantitative reconstruction of experimental measurements. Finally, we suggest a possible way forward via adoption of multiscale approaches and coarse-grained simulations as next steps toward efficient elucidation of ligand binding kinetics.

Macromolecule suppressed GABA levels show no relationship with age in a pediatric sample

The inhibitory neurotransmitter γ-Aminobutyric acid (GABA) plays a crucial role in cortical development. Therefore, characterizing changes in GABA levels during development has important implications for the study of healthy development and developmental disorders. Brain GABA levels can be measured non-invasively using GABA-edited magnetic resonance spectroscopy (MRS). However, the most commonly used editing technique to measure GABA results in contamination of the GABA signal with macromolecules (MM). Therefore, GABA measured using this technique is often referred to as GABA+ . While few in number, previous studies have shown GABA+ levels increase with age during development. However, these studies are unable to specify whether it is specifically GABA that is increasing or, instead, if levels of MM increase. In this study, we use a GABA-editing technique specifically designed to suppress the MM signal (MM-supp GABA). We find no relationship between MM-supp GABA and age in healthy children aged 7-14 years. These findings suggest that the relationship between GABA+ and age is driven by changes in MM levels, not by changes in GABA levels. Moreover, these findings highlight the importance of accounting for MM levels in MRS quantification.

RCSB Protein Data Bank: powerful new tools for exploring 3D structures of biological macromolecules for basic and applied research and education in fundamental biology, biomedicine, biotechnology, bioengineering and energy sciences

The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB), the US data center for the global PDB archive and a founding member of the Worldwide Protein Data Bank partnership, serves tens of thousands of data depositors in the Americas and Oceania and makes 3D macromolecular structure data available at no charge and without restrictions to millions of RCSB.org users around the world, including >660 000 educators, students and members of the curious public using PDB101.RCSB.org. PDB data depositors include structural biologists using macromolecular crystallography, nuclear magnetic resonance spectroscopy, 3D electron microscopy and micro-electron diffraction. PDB data consumers accessing our web portals include researchers, educators and students studying fundamental biology, biomedicine, biotechnology, bioengineering and energy sciences. During the past 2 years, the research-focused RCSB PDB web portal (RCSB.org) has undergone a complete redesign, enabling improved searching with full Boolean operator logic and more facile access to PDB data integrated with >40 external biodata resources. New features and resources are described in detail using examples that showcase recently released structures of SARS-CoV-2 proteins and host cell proteins relevant to understanding and addressing the COVID-19 global pandemic.

Analytical Ultracentrifugation for Analysis of Protein-Nucleic Acid Interactions

Analytical ultracentrifugation is a powerful tool to characterize interactions of macromolecules in solution. In sedimentation velocity experiments, the sedimentation of interaction partners and complexes can be monitored directly and can be used to characterize interactions quantitatively. As an example, we show how the interaction of the clamp loader subcomplex of DNA polymerase III from E. coli and a template/primer DNA saturated with single-stranded DNA-binding protein can be analyzed by analytical ultracentrifugation with fluorescence detection.

Scaffold-Based Delivery of CRISPR/Cas9 Ribonucleoproteins for Genome Editing

The simple and versatile CRISPR/Cas9 system is a promising strategy for genome editing in mammalian cells. Generally, the genome editing components, namely Cas9 protein and single-guide RNA (sgRNA), are delivered in the format of plasmids, mRNA, or ribonucleoprotein (RNP) complexes. In particular, non-viral approaches are desirable as they overcome the safety concerns posed by viral vectors. To control cell fate for tissue regeneration, scaffold-based delivery of genome editing components will offer a route for local delivery and provide possible synergistic effects with other factors such as topographical cues that are co-delivered by the same scaffold. In this chapter, we detail a simple method of surface modification to functionalize electrospun nanofibers with CRISPR/Cas9 RNP complexes. The mussel-inspired bio-adhesive coating will be used as it is a simple and effective method to immobilize biomolecules on the surface. Nanofibers will provide a biomimicking microenvironment and topographical cues to seeded cells. For evaluation, a model cell line with single copies of enhanced green fluorescent protein (U2OS.EGFP) will be used to validate the efficiency of gene disruption.

Integrative characterization of the near-minimal bacterium Mesoplasma florum

The near-minimal bacterium Mesoplasma florum is an interesting model for synthetic genomics and systems biology due to its small genome (~ 800 kb), fast growth rate, and lack of pathogenic potential. However, fundamental aspects of its biology remain largely unexplored. Here, we report a broad yet remarkably detailed characterization of M. florum by combining a wide variety of experimental approaches. We investigated several physical and physiological parameters of this bacterium, including cell size, growth kinetics, and biomass composition of the cell. We also performed the first genome-wide analysis of its transcriptome and proteome, notably revealing a conserved promoter motif, the organization of transcription units, and the transcription and protein expression levels of all protein-coding sequences. We converted gene transcription and expression levels into absolute molecular abundances using biomass quantification results, generating an unprecedented view of the M. florum cellular composition and functions. These characterization efforts provide a strong experimental foundation for the development of a genome-scale model for M. florum and will guide future genome engineering endeavors in this simple organism.

Mechanisms of Macromolecular Interactions Mediated by Protein Intrinsic Disorder

Intrinsically disordered proteins or regions (IDPs or IDRs) are widespread in the eukaryotic proteome. Although lacking stable three-dimensional structures in the free forms, IDRs perform critical functions in various cellular processes. Accordingly, mutations and altered expression of IDRs are associated with many pathological conditions. Hence, it is of great importance to understand at the molecular level how IDRs interact with their binding partners. In particular, discovering the unique interaction features of IDRs originating from their dynamic nature may reveal uncharted regulatory mechanisms of specific biological processes. Here we discuss the mechanisms of the macromolecular interactions mediated by IDRs and present the relevant cellular processes including transcription, cell cycle progression, signaling, and nucleocytoplasmic transport. Of special interest is the multivalent binding nature of IDRs driving assembly of multicomponent macromolecular complexes. Integrating the previous theoretical and experimental investigations, we suggest that such IDR-driven multiprotein complexes can function as versatile allosteric switches to process diverse cellular signals. Finally, we discuss the future challenges and potential medical applications of the IDR research.

Computational structure modeling for diverse categories of macromolecular interactions

Computational protein-protein docking is one of the most intensively studied topics in structural bioinformatics. The field has made substantial progress through over three decades of development. The development began with methods for rigid-body docking of two proteins, which have now been extended in different directions to cover the various macromolecular interactions observed in a cell. Here, we overview the recent developments of the variations of docking methods, including multiple protein docking, peptide-protein docking, and disordered protein docking methods.

A unified framework for packing deformable and non-deformable subcellular structures in crowded cryo-electron tomogram simulation

BACKGROUND

Cryo-electron tomography is an important and powerful technique to explore the structure, abundance, and location of ultrastructure in a near-native state. It contains detailed information of all macromolecular complexes in a sample cell. However, due to the compact and crowded status, the missing edge effect, and low signal to noise ratio (SNR), it is extremely challenging to recover such information with existing image processing methods. Cryo-electron tomogram simulation is an effective solution to test and optimize the performance of the above image processing methods. The simulated images could be regarded as the labeled data which covers a wide range of macromolecular complexes and ultrastructure. To approximate the crowded cellular environment, it is very important to pack these heterogeneous structures as tightly as possible. Besides, simulating non-deformable and deformable components under a unified framework also need to be achieved.

RESULT

In this paper, we proposed a unified framework for simulating crowded cryo-electron tomogram images including non-deformable macromolecular complexes and deformable ultrastructures. A macromolecule was approximated using multiple balls with fixed relative positions to reduce the vacuum volume. A ultrastructure, such as membrane and filament, was approximated using multiple balls with flexible relative positions so that this structure could deform under force field. In the experiment, 400 macromolecules of 20 representative types were packed into simulated cytoplasm by our framework, and numerical verification proved that our method has a smaller volume and higher compression ratio than the baseline single-ball model. We also packed filaments, membranes and macromolecules together, to obtain a simulated cryo-electron tomogram image with deformable structures. The simulated results are closer to the real Cryo-ET, making the analysis more difficult. The DOG particle picking method and the image segmentation method are tested on our simulation data, and the experimental results show that these methods still have much room for improvement.

CONCLUSION

The proposed multi-ball model can achieve more crowded packaging results and contains richer elements with different properties to obtain more realistic cryo-electron tomogram simulation. This enables users to simulate cryo-electron tomogram images with non-deformable macromolecular complexes and deformable ultrastructures under a unified framework. To illustrate the advantages of our framework in improving the compression ratio, we calculated the volume of simulated macromolecular under our multi-ball method and traditional single-ball method. We also performed the packing experiment of filaments and membranes to demonstrate the simulation ability of deformable structures. Our method can be used to do a benchmark by generating large labeled cryo-ET dataset and evaluating existing image processing methods. Since the content of the simulated cryo-ET is more complex and crowded compared with previous ones, it will pose a greater challenge to existing image processing methods.

Parameterization of metabolite and macromolecule contributions in interrelated MR spectra of human brain using multidimensional modeling

Macromolecular signals are crucial constituents of short echo-time ¹ H MR spectra with potential clinical implications in themselves as well as essential ramifications for the quantification of the usually targeted metabolites. Their parameterization, needed for general fitting models, is difficult because of their unknown composition. Here, a macromolecular signal parameterization together with metabolite signal quantification including relaxation properties is investigated by multidimensional modeling of interrelated 2DJ inversion-recovery (2DJ-IR) datasets. Simultaneous and iterative procedures for defining the macromolecular background (MMBG) as mono-exponentially or generally decaying signals over TE are evaluated. Varying prior knowledge and restrictions in the metabolite evaluation are tested to examine their impact on results and fitting stability for two sets of three-dimensional spectra acquired with metabolite-cycled PRESS from cerebral gray and white matter locations. One dataset was used for model optimization, and also examining the influence of prior knowledge on estimated parameters. The most promising model was applied to a second dataset. It turned out that the mono-exponential decay model appears to be inadequate to represent TE-dependent signal features of the MMBG. TE-adapted MMBG spectra were therefore determined. For a reliable overall quantification of implicated metabolite concentrations and relaxation times, a general fitting model had to be constrained in terms of the number of fitting variables and the allowed parameter space. With such a model in place, fitting precision for metabolite contents and relaxation times was excellent, while fitting accuracy is difficult to judge and bias was likely influenced by the type of fitting constraints enforced. In summary, the parameterization of metabolite and macromolecule contributions in interrelated MR spectra has been examined by using multidimensional modeling on complex 2DJ-IR datasets. A tightly restricted model allows fitting of individual subject data with high fitting precision documented in small Cramér-Rao lower bounds, good repeatability values and a relatively small spread of estimated concentration and relaxation values for a healthy subject cohort.