Subspace-based parameter estimation of exponentially damped sinusoids using prior knowledge of frequency and phase

Variable screening is a powerful and efficient tool for dimension reduction under ultrahigh dimensional settings. However, most existing methods overlook useful prior knowledge in specific applications. In this work, from a Bayesian modeling perspective, we develop a unified variable screening procedure for the linear regression model. We discuss different constructions of posterior mean screening (PMS) statistics to incorporate different types of prior knowledge according to specific applications. With non-informative prior specifications, PMS is equivalent to high-dimensional ordinary least-square projections (HOLP). We establish the screening consistency property for PMS with different types of prior knowledge. We show that PMS is robust to prior misspecifications; and when the prior knowledge provides correct information on summarizing the true parameter settings, PMS can substantially improve the selection accuracy compared to HOLP and other existing methods. We illustrate our method with extensive simulation studies and an analysis of neuroimaging data.

As discussed in the research of Mohamed et al. (2013), learning and studying via a different context, including the inter-cultural knowledge of a teacher, may present a challenge when trying to account for students’ prior knowledge. Enhancing their study, this paper addresses the question of whether or not an internal session comprising open discussion and brainstorming followed by asynchronous commenting and ending with self-reflection might help to assess students’ prior knowledge. Data was collected in the context of a series of academic teachings partly supported by the METIS project (The METIS Project is funded by the national German Federal Ministry of Science and Research, cp.: http://www.ihi.zittau.de/cms/de/621/Forschung.) in two separate phases. Graduate students on master level attended the phase reported here in order to study research methods as a joint activity of Technische Universitat Dresden, and Internationales Hochschulinstitut Zittau, both Germany. For the experimental group, the study found that there are no significant differences between the control and treatment group in terms of cognitive achievement and students’ attitudes. From the teacher’s perspective, however, this course is learning atmosphere challenged students’ reactions. Design is suggested to be enhanced to allow a closer look on different types of prior knowledge in the field of research training.

Detailed knowledge of the structure of bio molecules with atomic resolution is essential for the understanding of their function. Moreover the identification and quantification of their dynamic processes are important, as they are the origin of molecular functionalities. Different spectroscopic methods like X-ray crystallography (limited to structure elucidation, no dynamics), mass spectroscopy, electron spin resonance (EPR) and nuclear magnetic resonance (NMR) spectroscopy can deliver this detailed structural information. Especially NMR spectroscopy has found its application in the identification of dynamic processes. This thesis was focused on the characterization of dynamic processes, the structure elucidation of natural products available in nanograms and the synthesis of lanthanide chelating tags for the study of protein-ligand and protein-protein interactions in solution. The thesis is divided into three chapters addressing a specific task of the mentioned topic. A: The influences of different donors and linkers on lanthanide chelating tags were investigated. A 4S-Tetramethylcyclen was used as enantiomerically pure core molecule. The side chains were based on enantiopure lactic acid derivatives. The carboxylic acids of lactic acid were transformed into different functional groups like thiols, nitrogens, and carbonyl. These different donor groups are expected to change the magnetic susceptibility tensor of the lanthanide cation in complex with the synthesized tags. Special protection protocols for the introduction of heteroatoms are presented. On this basis also two new linkers were introduced. These linkers bind in a selective way to cysteins on a protein surface as thioethers. The alpha-bromoketones are very selective for the coupling to cysteins, nevertheless they have a tendency to hydrolyse under Lewis acidic conditions. Vinylsulfones require harsher tagging conditions but they are much more stable against hydrolysis. All new tags were attached to proteins and tested as PCS reagents in protein NMR spectroscopy. B: The effects of para-substituents on the rotation barrier of 2,2«-propyl and 2,2«-butyl-bridged biphenyls were studied by dynamic NMR spectroscopy and dynamic HPLC measurements. Gibbs free activation energies of the rotation about the central biphenyl bond were estimated by variable temperature 1H-NMR experiments for the propyl bridged biphenyl. The resulting data were correlated to Hammett-parameters ?P as a measure of electron donor and acceptor strength. It was demonstrated that the electronic effects influence the activation barrier significantly, whereas sterics had only minor influence. Rate constants were calculated from line shape analysis and analysed by Eyring plots to calculate the entropic and enthalpic contributions. Thermodynamic data for the butyl-bridged biphenyls were directly obtained from dynamic HPLC chromatograms. DFT calculations delivered different transition states for the two series of biphenyls. The calculation of the activation parameters showed a similar trend and therefore the model is validated. The differences in the enthalpic and entropic contributions between HPLC, NMR and DFT calculations are method dependent, which was proven by changes of the solvent in NMR experiments that led to alteration of these contributions. C: The identification and total synthesis of a novel methylated lipid antigen (mLPA) was performed. The presented mLPA shows potent inhibition properties against human leukaemia. A combination of extraction protocols, activation essays and HPLC-MS measurements were used to identify the different antigen molecules from cell extracts. Three different candidates were identified. MS-MS experiments delivered structural insights, which were further confirmed by NMR spectroscopy and allowed the characterization of two of these structures. Total syntheses of the identified structures were performed in 6 linear steps. The high biological activity of the synthesized structures corroborated the identity of the active molecule.

Nuclear magnetic resonance (NMR) spectroscopy is one of the most powerful analytical techniques available to biology. This review is an introduction to the potential of this method and is aimed at readers who have little or no experience in acquiring or analyzing NMR spectra. We focus on spectroscopic applications of the magnetic resonance effect, rather than imaging ones, and explain how various aspects of the NMR phenomenon make it a versatile tool with which to address a number of biological problems. Using detailed examples, we discuss the use of (1) H NMR spectroscopy in mixture analysis and metabolomics, the use of (13) C NMR spectroscopy in tracking isotopomers and determining the flux through metabolic pathways ('fluxomics') and the use of (31) P NMR spectroscopy in monitoring ATP generation and intracellular pH homeotasis in vivo. Further examples demonstrate how NMR spectroscopy can be used to probe the physical environment of a cell by measuring diffusion and the tumbling rates of individual metabolites and how it can determine macromolecular structures by measuring the bonds and distances which separate individual atoms. We finish by outlining some of the key challenges which remain in NMR spectroscopy and we highlight how recent advances-such as increased magnet field strengths, cryogenic cooling, microprobes and hyperpolarisation-are opening new avenues for today's biological NMR spectroscopists.

A nuclear magnetic resonance advance. Imaging fluorinated anesthetics in the brain.

Facilitated by the powerful feature extraction ability of neural networks, deep clustering has achieved great success in analyzing high-dimensional and complex real-world data. The performance of deep clustering methods is affected by various factors such as network structures and learning objectives. However, as pointed out in this survey, the essence of deep clustering lies in the incorporation and utilization of prior knowledge, which is largely ignored by existing works. From pioneering deep clustering methods based on data structure assumptions to recent contrastive clustering methods based on data augmentation invariances, the development of deep clustering intrinsically corresponds to the evolution of prior knowledge. In this survey, we provide a comprehensive review of deep clustering methods by categorizing them into six types of prior knowledge. We find that in general the prior innovation follows two trends, namely, i) from mining to constructing, and ii) from internal to external. Besides, we provide a benchmark on five widely-used datasets and analyze the performance of methods with diverse priors. By providing a novel prior knowledge perspective, we hope this survey could provide some novel insights and inspire future research in the deep clustering community.

Protein-ligand interactions lie at the heart of most biological and medical processes. To lay the groundwork for a mechanistic understanding of complex biological networks, a detailed description of the associated proteins, their roles, and their interaction partners is essential. Furthermore, a detailed description of protein-ligand interactions is of pharmaceutical interest, as small molecules targeting proteins constitute the basis for the treatment of numerous medical conditions. In this thesis, we used nuclear magnetic resonance (NMR) spectroscopy to probe the conformational properties of biologically and pharmaceutically essential proteins, either alone or complexed with small molecules, to reveal the mechanistic grounds of these interactions. The first chapter entails the structural investigation of Tumor necrosis factor-alpha (TNFα) by NMR spectroscopy. TNFα is a homotrimeric protein that enjoys tremendous scientific and pharmaceutical interest due to its pivotal role in the human immune response. However, its overexpression leads to numerous chronic inflammatory diseases. Studying the interaction between TNFα and small molecular inhibitors is thus of utmost importance if better cures for these diseases are to be found. Here, we investigated active and inhibited forms of TNFα in solution by NMR spectroscopy and showed that TNFα exhibits significant conformational exchange, especially in the receptor binding site and the trimer interface, which is crucial for its biological activity. Inhibition of TNFα by perturbing the trimer interface, either by mutagenesis or by targeting it with small molecules, does not lead to disruption of the postulated trimer in solution. Instead, it induces a significant increase in the conformational dynamics of TNFα propagating from the trimer interface to the receptor-binding site. Therefore, we propose that an allosteric dynamic coupling between the trimer interface and the active site mediates inhibition. This provides novel insights into the mechanisms of TNFα inhibition, which in turn may lead to the development of better-suited drug assays against this highly important molecule. The second chapter presents the study of alpha acid glycoprotein-1 (AGP1) by NMR. The heavily glycosylated AGP1 is one of the two most abundant human serum proteins and binds various metabolites as well as, perhaps most interestingly from a pharmaceutical perspective, many administered drugs. Understanding the interaction between AGP1 and small molecules on a molecular level in addition to revealing the yet unclear impact of the appended glycans in this process is thus of great importance - as drug binding to plasma proteins modulates their pharmacokinetics and pharmacodynamics. In this thesis, efficient protocols were developed which enabled us to shed light on the influence of glycosylation on the structure of AGP1 and to characterize its ligand binding at a level of detail which had not yet been achieved. We showed that glycosylation affects the protein conformation in the vicinity of the glycosylation site, and provide evidence for a conformational rearrangement upon binding of small molecules. By giving these novel insights, our results contribute to the functional understanding of AGP1 and more broadly to the relatively unexplored class of glycoproteins. The third chapter discusses the combination of our measured NMR data (presented in chapters one and two) with DNA-encoded chemical libraries (DECL) in drug discovery. DECL allows for the efficient identification of potential small molecule binders, while our concomitant NMR data provide the framework for assisting both the validation of ‘hits’ and the optimization process. We could confirm interactions between TNFα or AGP1 and binders identified by DECL. Here, the first application of this approach for drug discovery for TNFα and AGP1 is presented. In summary, our study contributes to a better understanding of two highly relevant proteins: AGP1 and TNFα. The data presented provides original insights into the inhibition mechanisms of small molecules and revealed the importance of conformational dynamics in these processes. Finally, our results will add a new aspect to the complex process of rational drug development, which will ultimately benefit many patients affected by diverse medical conditions.

The Biological Magnetic Resonance Data Bank (BioMagResBank or BMRB), founded in 1988, serves as the archive for data generated by nuclear magnetic resonance (NMR) spectroscopy of biological systems. NMR spectroscopy is unique among biophysical approaches in its ability to provide a broad range of atomic and higher-level information relevant to the structural, dynamic, and chemical properties of biological macromolecules, as well as report on metabolite and natural product concentrations in complex mixtures and their chemical structures. BMRB became a core member of the Worldwide Protein Data Bank (wwPDB) in 2007, and the BMRB archive is now a core archive of the wwPDB. Currently, about 10% of the structures deposited into the PDB archive are based on NMR spectroscopy. BMRB stores experimental and derived data from biomolecular NMR studies. Newer BMRB biopolymer depositions are divided about evenly between those associated with structure determinations (atomic coordinates and supporting information archived in the PDB) and those reporting experimental information on molecular dynamics, conformational transitions, ligand binding, assigned chemical shifts, or other results from NMR spectroscopy. BMRB also provides resources for NMR studies of metabolites and other small molecules that are often macromolecular ligands and/or nonstandard residues. This chapter is directed to the structural biology community rather than the metabolomics and natural products community. Our goal is to describe various BMRB services offered to structural biology researchers and how they can be accessed and utilized. These services can be classified into four main groups: (1) data deposition, (2) data retrieval, (3) data analysis, and (4) services for NMR spectroscopists and software developers. The chapter also describes the NMR-STAR data format used by BMRB and the tools provided to facilitate its use. For programmers, BMRB offers an application programming interface (API) and libraries in the Python and R languages that enable users to develop their own BMRB-based tools for data analysis, visualization, and manipulation of NMR-STAR formatted files. BMRB also provides users with direct access tools through the NMRbox platform.

Chapter 1 of this thesis provides an overview of the structure and function of proteins as well as their investigation via NMR spectroscopy. Proteins are one of the most important building blocks of life. They are part of every organism and fulfill a variety of functions including, for example, the catalysis of many chemical reactions, which is the reason various processes in an organism become possible in the first place. Proteins are made up of amino acids, which are linked together via peptide bonds during the protein biosynthesis. The 22 proteinogenic amino acids result in an almost unlimited number of sequential combinations that give proteins their versatility. The sequence of amino acids in a protein is also called the primary structure. From this, locally limited structural motifs such as α-helices and β-sheets are formed, representing the secondary structure. Further intramolecular interactions create the tertiary structure of a protein, which can be seen as the overall three-dimensional structure of the protein. Furthermore, several individual proteins can assemble into a larger complex to form a quaternary structure. There are various methods for investigating the structure of proteins, including nuclear magnetic resonance (NMR) spectroscopy. In NMR spectroscopy, atomic nuclei with a non-zero nuclear spin are polarized by a constant magnetic field and then excited using radio frequency pulses. The emitted resonance frequencies are detected in the form of a free induction decay (FID) and converted into an NMR spectrum by a Fourier transformation. Many NMR experiments are available for researching proteins. By default, a two-dimensional 1H15N-HSQC spectrum is measured, which provides signals for each N-H bond in a protein meaning that one signal is obtained for each N-H in the backbone of the amino acids. Using 3D NMR experiments, these signals can then be assigned to the respective amino acids in the protein sequence. This makes it possible to investigate the dynamics of proteins as well as the formation of complexes with a ligand or another biomacromolecule if they interact. Further 3D NMR experiments also make it possible to assign the side-chains of the protein. With the help of the determined resonance assignments and spatial information from various NOESY spectra, a protein structure can then be calculated using a suitable computer program. Recently, the prediction of protein structures using AI (artificial intelligence)-supported programs has also become more prevalent. In particular, the artificial neural network AlphaFold has been extremely successful in predicting correct structures without any experimental data provided by the user. Chapter 2 of this thesis introduces the research field of small proteins. These are proteins with a length of usually less than 100 amino acids, although definitions in literature vary and upper limits of, for example, 50 or 200 amino acids exist as well. Various other names are also used to describe small proteins, such as μ-proteins or sORF-encoded peptides. The field of small proteins is still relatively new, as they were overlooked in research for many years. One reason for this was the lower limit of 100 codons that was set for the identification of open reading frames (ORFs) in genome projects. This served to exclude numerous biologically irrelevant ORFs from genome annotation. However, this meant that functional ORFs coding for small proteins were also ignored. Another reason was that experimental methods were not designed for the analysis of small proteins, meaning they could often not be detected at all. However, new analytical methods such as ribosome profiling and a generally increased focus on the detection of small proteins have led to their detection in all domains of life. In the research group of Prof. Dr. Schwalbe, small proteins of various prokaryotes were structurally characterized as part of a special priority program by the DFG. NMR spectroscopy was primarily used for this purpose, as it is the method of choice for the investigation of small proteins. The results of this research were published in several articles, two of which are part of this dissertation.

Wine authentication is vital in identifying malpractice and fraud, and various physical and chemical analytical techniques have been employed for this purpose. Besides wet chemistry, these include chromatography, isotopic ratio mass spectrometry, optical spectroscopy, and nuclear magnetic resonance (NMR) spectroscopy, which have been applied in recent years in combination with chemometric approaches. For many years, 2 H NMR spectroscopy was the method of choice and achieved official recognition in the detection of sugar addition to grape products. Recently, 1 H NMR spectroscopy, a simpler and faster method (in terms of sample preparation), has gathered more and more attention in wine analysis, even if it still lacks official recognition. This technique makes targeted quantitative determination of wine ingredients and nontargeted detection of the metabolomic fingerprint of a wine sample possible. This review summarizes the possibilities and limitations of 1 H NMR spectroscopy in analytical wine authentication, by reviewing its applications as reported in the literature. Examples of commercial and open-source solutions combining NMR spectroscopy and chemometrics are also examined herein, together with its opportunities of becoming an official method.

To determine whether invasive breast cancer can be distinguished from benign lesions with proton magnetic resonance (MR) spectroscopy ex vivo on the basis of altered cellular chemistry. Two hundred eighteen fine-needle biopsy specimens were obtained in 191 patients undergoing surgery and were analyzed with proton MR spectroscopy. MR spectroscopic and histopathologic findings were compared. Invasive carcinoma produced increased signal at 3.25 ppm, attributable to choline-containing metabolites. Discrimination between invasive carcinoma (n = 82), benign lesions (n = 106), or carcinoma in situ (n = 17) was based on the resonance intensity at 3.25 ppm standardized to the resonance at 3.05 ppm (P < .001). The ratio of peak height intensities of resonances at 3.25 to those at 3.05 ppm was less than 1.7 in 102 of the 106 normal or benign lesions. All carcinoma in situ specimens with comedonecrosis or a microinvasive component (n = 6) were categorized at MR spectroscopy with invasive carcinoma, while others with in situ disease alone were categorized with benign lesions (n = 11). The sensitivity and specificity of MR spectroscopy in fine-needle biopsy specimens in distinguishing benign lesions from invasive cancer were 95% and 96%, respectively. Proton MR spectroscopy of fine-needle biopsy specimens provides objective diagnostic information that complements findings of conventional preoperative investigations of breast lesions.

Solid-state nuclear magnetic resonance (NMR) spectroscopy is an atomic-level method used to determine the chemical structure, three-dimensional structure, and dynamics of solids and semi-solids. This Primer summarizes the basic principles of NMR as applied to the wide range of solid systems. The fundamental nuclear spin interactions and the effects of magnetic fields and radiofrequency pulses on nuclear spins are the same as in liquid-state NMR. However, because of the anisotropy of the interactions in the solid state, the majority of high-resolution solid-state NMR spectra is measured under magic-angle spinning (MAS), which has profound effects on the types of radiofrequency pulse sequences required to extract structural and dynamical information. We describe the most common MAS NMR experiments and data analysis approaches for investigating biological macromolecules, organic materials, and inorganic solids. Continuing development of sensitivity-enhancement approaches, including 1H-detected fast MAS experiments, dynamic nuclear polarization, and experiments tailored to ultrahigh magnetic fields, is described. We highlight recent applications of solid-state NMR to biological and materials chemistry. The Primer ends with a discussion of current limitations of NMR to study solids, and points to future avenues of development to further enhance the capabilities of this sophisticated spectroscopy for new applications.

In recent years, increasing application of nuclear magnetic resonance (NMR) spectroscopy in the study of the agricultural food products has been remarked, thanks to the advantages of this technique over other conventional analytical techniques. This preliminary work presents, for the first time, the application of an innovative NMR technique, the proton high resolution magic angle spinning (1H HR-MAS), for studying meat features. It stresses that this method makes it possible to acquire qualitative and quantitative information about chemical composition, both quickly and without any particular preparation of the sample to be analysed. Finally, the study highlights the potentiality of this method in defining the origin of meat and the possibility of identifying meat adulteration.

Characterization of grafting properties of ABS latexes: ATR-FTIR vs NMR spectroscopy

Phenolic moieties strongly influence lignin reactivity and physical properties, and thus accurate quantification of phenolic groups in lignin is a critical analytical chemistry need. Today, 31P nuclear magnetic resonance (NMR) spectroscopy is widely considered the standard method to this end, but this approach uses a hazardous and expensive derivatization agent, and the NMR spectroscopy experiments are time consuming due to long relaxation times. Here, we report a complementary method that enables accurate identification and quantification of phenolic groups in lignin samples using pentafluoropyridine (PFP) as a derivatizing reagent followed by 19F NMR spectroscopy. Using dimethyl sulfoxide as a solvent in the presence of K2CO3, phenolic hydroxyl groups in lignin model compounds were fully converted to the corresponding tetrafluoropyridyl-ether products within 1 min. PFP exhibits high selectivity for the reaction with phenolic hydroxyl groups relative to aliphatic alcohols, and we show that side reactions with carboxylic acids, if present, can be avoided through the addition of 40% water to the reaction solvent. The PFP 19F method achieved similar results compared to 31P NMR spectroscopy when applied to reductive catalytic fractionation oil from poplar, softwood kraft lignin, and corn stover milled wood lignin, thereby offering a safe and cost-effective method for phenolic measurements in lignin.