Axial Spondyloarthritis: an overview of the disease.

Axial Spondyloarthritis (axSpA) is a chronic, inflammatory, immune-mediated rheumatic disease that comprises two subsets, non-radiographic and radiographic axSpA, and belongs to a heterogeneous group of spondyloarthritides (SpA). Over the years, the concept of SpA has evolved significantly, as reflected in the existing classification criteria. Considerable progress has been made in understanding the genetic and immunological basis of axSpA, in studying the processes of chronic inflammation and pathological new bone formation, which are pathognomonic for the disease. As a result, new medication therapies were developed, which bring more effective ways for disease control. This review presents a brief overview of the literature related to these aspects of disease after summarising the available information on the topic that we considered relevant. Specifically, it delves into recent research illuminating the primary pathological processes of enthesitis and associated osteitis in the context of inflammation in axSpA. The exploration extends to discussion of inflammatory pathways, with a particular focus on Th1/Th17-mediated immunity and molecular signaling pathways of syndesmophyte formation. Additionally, the review sheds light on the pivotal role of cytokine dysregulation, highlighting the significance of the IL-23/17 axis and TNF-α in this intricate network of immune responses which is decisive for therapeutic approaches in the disease.

Tumor-Derived Antigenic Peptides as Potential Cancer Vaccines.

Peptide antigens derived from tumors have been observed to elicit protective immune responses, categorized as either tumor-associated antigens (TAAs) or tumor-specific antigens (TSAs). Subunit cancer vaccines incorporating these antigens have shown promise in inducing protective immune responses, leading to cancer prevention or eradication. Over recent years, peptide-based cancer vaccines have gained popularity as a treatment modality and are often combined with other forms of cancer therapy. Several clinical trials have explored the safety and efficacy of peptide-based cancer vaccines, with promising outcomes. Advancements in techniques such as whole-exome sequencing, next-generation sequencing, and in silico methods have facilitated the identification of antigens, making it increasingly feasible. Furthermore, the development of novel delivery methods and a deeper understanding of tumor immune evasion mechanisms have heightened the interest in these vaccines among researchers. This article provides an overview of novel insights regarding advancements in the field of peptide-based vaccines as a promising therapeutic avenue for cancer treatment. It summarizes existing computational methods for tumor neoantigen prediction, ongoing clinical trials involving peptide-based cancer vaccines, and recent studies on human vaccination experiments.

Viral Immunogenicity Prediction by Machine Learning Methods.

Since viruses are one of the main causes of infectious illnesses, prophylaxis is essential for efficient disease control. Vaccines play a pivotal role in mitigating the transmission of various viral infections and fortifying our defenses against them. The initial step in modern vaccine design and development involves the identification of potential vaccine targets through computational techniques. Here, using datasets of 1588 known viral immunogens and 468 viral non-immunogens, we apply machine learning algorithms to develop models for the prediction of protective immunogens of viral origin. The datasets are split into training and test sets in a 4:1 ratio. The protein structures are encoded by E-descriptors and transformed into uniform vectors by the auto- and cross-covariance methods. The most relevant descriptors are selected by the gain/ratio technique. The models generated by Random Forest, Multilayer Perceptron, and XGBoost algorithms demonstrate superior predictive performance on the test sets, surpassing predictions made by VaxiJen 2.0-an established gold standard in viral immunogenicity prediction. The key attributes determining immunogenicity in viral proteins are specific fingerprints in hydrophobicity and steric properties.

Modeling Peptide-Protein Interactions by a Logo-Based Method: Application in Peptide-HLA Binding Predictions.

Peptide-protein interactions form a cornerstone in molecular biology, governing cellular signaling, structure, and enzymatic activities in living organisms. Improving computational models and experimental techniques to describe and predict these interactions remains an ongoing area of research. Here, we present a computational method for peptide-protein interactions' description and prediction based on leveraged amino acid frequencies within specific binding cores. Utilizing normalized frequencies, we construct quantitative matrices (QMs), termed 'logo models' derived from sequence logos. The method was developed to predict peptide binding to HLA-DQ2.5 and HLA-DQ8.1 proteins associated with susceptibility to celiac disease. The models were validated by more than 17,000 peptides demonstrating their efficacy in discriminating between binding and non-binding peptides. The logo method could be applied to diverse peptide-protein interactions, offering a versatile tool for predictive analysis in molecular binding studies.

Correction: Popova et al. Ni-Cu and Ni-Co-Modified Fly Ash Zeolite Catalysts for Hydrodeoxygenation of Levulinic Acid to γ-Valerolactone. Molecules 2024, 29, 99.

Error in Figure [...].

CEST-MRI for body oncologic imaging: are we there yet?

Chemical exchange saturation transfer (CEST) MRI has gained recognition as a valuable addition to the molecular imaging and quantitative biomarker arsenal, especially for characterization of brain tumors. There is also increasing interest in the use of CEST-MRI for applications beyond the brain. However, its translation to body oncology applications lags behind those in neuro-oncology. The slower migration of CEST-MRI to non-neurologic applications reflects the technical challenges inherent to imaging of the torso. In this review, we discuss the application of CEST-MRI to oncologic conditions of the breast and torso (i.e., body imaging), emphasizing the challenges and potential solutions to address them. While data are still limited, reported studies suggest that CEST signal is associated with important histology markers such as tumor grade, receptor status, and proliferation index, some of which are often associated with prognosis and response to therapy. However, further technical development is still needed to make CEST a reliable clinical application for body imaging and establish its role as a predictive and prognostic biomarker.

Assessment of Novel Proteins Triggering Celiac Disease via Docking-Based Approach.

Human leukocyte antigens (HLAs) are pivotal in antigen processing, presenting to CD4+ T cells, and are linked to autoimmune disease susceptibility. In celiac disease, HLA-DQ2.5 and HLA-DQ8.1 bind gluten peptides on APCs, some recognized by CD4+ T cells, prompting inflammation and tissue damage. While extensively studied experimentally, these alleles lack comprehensive in silico analysis. To explore peptide-HLA preferences, we used molecular docking on peptide libraries, deriving quantitative matrices (QMs) for evaluating amino acids at nine-residue peptide binding cores. Our findings tie specific residue preferences to peptide backbone conformations. Validating QMs on known binders and non-binders showed strong predictive power (89-94% accuracy). These QMs excel in screening protein libraries, even whole proteomes, notably reducing time and costs for celiac disease risk assessment in novel proteins. This computational approach aligns with European Food Safety Authority guidance, promising efficient screening for potential celiac disease triggers.

Ni-Cu and Ni-Co-Modified Fly Ash Zeolite Catalysts for Hydrodeoxygenation of Levulinic Acid to γ-Valerolactone.

Monometallic (Ni, Co, Cu) and bimetallic (Ni-Co, Ni-Cu) 10-20 wt.% metal containing catalysts supported on fly ash zeolite were prepared by post-synthesis impregnation method. The catalysts were characterized by X-ray powder diffraction, N2 physisorption, XPS and H2-TPR methods. Finely dispersed metal oxides and mixed oxides were detected after the decomposition of the impregnating salt on the relevant zeolite support. Via reduction intermetallic, NiCo and NiCu phases were identified in the bimetallic catalysts. The catalysts were studied in hydrodeoxygenation of lignocellulosic biomass-derived levulinic acid to γ-valerolactone (GVL) in a batch system by water as a solvent. Bimetallic, 10 wt.% Ni, and 10 wt.% Cu or Co containing fly ash zeolite catalysts showed higher catalytic activity than monometallic ones. Their selectivity to GVL reached 70-85% at about 100% conversion. The hydrogenation activity of catalysts was found to be stronger compared to their hydration ability; therefore, the reaction proceeds through formation of 4-hydroxy pentanoic acid as the only intermediate compound.

Virtual Screening and Hit Selection of Natural Compounds as Acetylcholinesterase Inhibitors.

Acetylcholinesterase (AChE) is one of the classical targets in the treatment of Alzheimer's disease (AD). Inhibition of AChE slows down the hydrolysis of acetycholine and increases choline levels, improving the cognitive function. The achieved success of plant-based natural drugs acting as AChE inhibitors, such as galantamine (GAL) from Galanthus genus and huperzine A from Huperzia serrate (approved drug in China), in the treatment of AD, and the fact that natural compounds (NCs) are considered as safer and less toxic compared to synthetic drugs, led us to screen the available NCs (almost 150,000) in the ZINC12 database for AChE inhibitory activity. The compounds were screened virtually by molecular docking, filtered for suitable ADME properties, and 32 ligands from 23 structural groups were selected. The stability of the complexes was estimated via 1 µs molecular dynamics simulation. Ten compounds formed stable complexes with the enzyme and had a vendor and a reasonable price per mg. They were tested for AChE inhibitory and antioxidant activity. Five compounds showed weak AChE inhibition and three of them exhibited high antioxidant activity.

A retrofit to enable dynamic B1+ steering for transmit arrays without multiple amplifiers.

PURPOSE: B1+ shimming is an important method for mitigating B1 inhomogeneity in high-field MRI. Using independent power amplifiers for each transmit (Tx) element is the preferred method for B1 shimming but comes with a high cost. Conversely, the simplest approach to control a Tx array is by using coaxial cables of varying length in the Tx chain, but this approach is cumbersome and impractical for dynamic shimming. In this article, a system is described that enables dynamic, phase-only, eight-channel B1+ steering on a 7T MR scanner with only two power amplifiers. METHODS: Power dividers were utilized to first split the existing two-channel Tx signal into eight channels. Digitally controlled phase shifters on each channel were designed to provide independent phase shifts with a resolution of 22.5° (from 0°, 22.5° … 337.5°). To validate the system, an eight-channel body dipole array was simulated and constructed for bench and 7T imaging and evaluation. RESULTS: The phase conjugate B1+ steering method was employed at three different spatial positions in simulation, bench measurements, and scanner measurements-all with matching results. At the desired points, regions with homogenous B1+ were generated, indicating good Tx steering to the selected region. CONCLUSION: The described system can be used as a simple retrofit to existing hardware to provide phase control while avoiding the need to manually switch cables and without requiring independent power amplifiers for each channel, thus demonstrating the ability to perform dynamic B1+ shimming with increased degrees of freedom but without significantly increased hardware cost.

A 32-channel receive array coil for bilateral breast imaging and spectroscopy at 7T.

PURPOSE: This work describes the construction and evaluation of a bilateral 32-channel receive array for breast imaging at 7T. METHODS: The receive array consisted of 32 receive coils, placed on two 3D-printed hemispherical formers. Each side of the receive array consisted of 16 receive loops, each loop having a corresponding detachable board with match/tune capacitors, active detuning circuitry, and a balun. Coil performance was evaluated on homogeneous canola oil phantoms using a Philips Achieva 7T system. Array coil performance was compared with a bilateral forced current excitation volume coil in transmit/receive mode and with a previously reported 16-channel unilateral coil with a similar design. RESULTS: The 32-channel array had an increase in average SNR throughout both phantoms by a factor of five as compared with the volume coil, with SNR increases up to 10 times along the periphery and three times in the center. Noise measurements showed low interelement noise correlation (average: 5.4%; maximum: 16.8%). Geometry factor maps were acquired for various acceleration factors and showed mean geometry factors <1.2, for combined acceleration factors of up to six. CONCLUSIONS: The improvements achieved demonstrate the clear potential for use in dynamic contrast-enhanced or diffusion-weighted MR studies, while maintaining diagnostically relevant spatial and temporal resolutions.

Combining inhomogeneous magnetization transfer and multipoint Dixon acquisition: Potential utility and evaluation.

PURPOSE: The recently introduced inhomogeneous magnetization transfer (ihMT) method has predominantly been applied for imaging the central nervous system. Future applications of ihMT, such as in peripheral nerves and muscles, will involve imaging in the vicinity of adipose tissues. This work aims to systematically investigate the partial volume effect of fat on the ihMT signal and to propose an efficient fat-separation method that does not interfere with ihMT measurements. METHODS: First, the influence of fat on ihMT signal was studied using simulations. Next, the ihMT sequence was combined with a multi-echo Dixon acquisition for fat separation. The sequence was tested in 9 healthy volunteers using a 3T human scanner. The ihMT ratio (ihMTR) values were calculated in regions of interest in the brain and the spinal cord using standard acquisition (no fat saturation), water-only, in-phase, and out-of-phase reconstructions. The values obtained were compared with a standard fat suppression method, spectral presaturation with inversion recovery. RESULTS: Simulations showed variations in the ihMTR values in the presence of fat, depending on the TEs used. The IhMTR values in the brain and spinal cord derived from the water-only ihMT multi-echo Dixon images were in good agreement with values from the unsuppressed sequence. The ihMT-spectral presaturation with inversion recovery combination resulted in 24%-35% lower ihMTR values compared with the standard non-fat-suppressed acquisition. CONCLUSION: The presence of fat within a voxel affects the ihMTR calculations. The IhMT multi-echo Dixon method does not compromise the observable ihMT effect and can potentially be used to remove fat influence in ihMT.

Spectral fitting strategy to overcome the overlap between 2-hydroxyglutarate and lipid resonances at 2.25 ppm.

PURPOSE: 1 H MRS provides a noninvasive tool for identifying mutations in isocitrate dehydrogenase (IDH). Quantification of the prominent 2-hydroxyglutarate (2HG) resonance at 2.25 ppm is often confounded by the lipid resonance at the same frequency in tumors with elevated lipids. We propose a new spectral fitting approach to separate these overlapped signals, therefore, improving 2HG evaluation. METHODS: TE 97 ms PRESS was acquired at 3T from 42 glioma patients. New lipid basis sets were created, in which the small lipid 2.25-ppm signal strength was preset with reference to the lipid signal at 0.9 ppm, incorporating published fat relaxation data. LCModel fitting using the new lipid bases (Fitting method 2) was conducted along with fitting using the LCModel built-in lipid basis set (Fitting method 1), in which the lipid 2.25-ppm signal is assessed with reference to the lipid 1.3-ppm signal. In-house basis spectra of low-molecular-weight metabolites were used in both fitting methods. RESULTS: Fitting method 2 showed marked improvement in identifying IDH mutational status compared with Fitting method 1. 2HG estimates from Fitting method 2 were overall smaller than those from Fitting method 1, which was because of differential assignment of the signal at 2.25 ppm to lipids. In receiver operating characteristic analysis, Fitting method 2 provided a complete distinction between IDH mutation and wild-type whereas Fitting method 1 did not. CONCLUSION: The data suggest that 1 H MR spectral fitting using the new lipid basis set provides a robust fitting strategy that improves 2HG evaluation in brain tumors with elevated lipids.

Effects of Curcumin and Ferulic Acid on the Folding of Amyloid-ß Peptide.

The polyphenols curcumin (CU) and ferulic acid (FA) are able to inhibit the aggregation of amyloid-ß (Aß) peptide with different strengths. CU is a strong inhibitor while FA is a weaker one. In the present study, we examine the effects of CU and FA on the folding process of an Aß monomer by 1 µs molecular dynamics (MD) simulations. We found that both inhibitors increase the helical propensity and decrease the non-helical propensity of Aß peptide. They prevent the formation of a dense bulk core and shorten the average lifetime of intramolecular hydrogen bonds in Aß. CU makes more and longer-lived hydrogen bonds, hydrophobic, π-π, and cation-π interactions with Aß peptide than FA does, which is in a good agreement with the observed stronger inhibitory activity of CU on Aß aggregation.

Turbo Spin-Echo Diffusion-Weighted Imaging in Prostate Magnetic Resonance Imaging of Men With Pelvic Hardware.

We evaluated an alternative diffusion-weighted imaging (DWI) acquisition for prostate magnetic resonance imaging of men with pelvic hardware, using radial k-space sampling (MultiVane [MV]), short-tau inversion-recovery (STIR) fat suppression, and split acquisition of turbo spin-echo signals. The optimized STIR-MV-DWI reduced metal-associated artifacts and image distortion, and aided in visualization of the prostate and lesions. The STIR-MV-DWI can be a valuable adjunct in prostate magnetic resonance imaging of men with pelvic hardware, among whom the conventional echo-planar DWI is compromised.

Accelerating chemical exchange saturation transfer MRI with parallel blind compressed sensing.

PURPOSE: Chemical exchange saturation transfer is a novel and promising MRI contrast method, but it can be time-consuming. Common parallel imaging methods, like SENSE, can lead to reduced quality of CEST. Here, parallel blind compressed sensing (PBCS), combining blind compressed sensing (BCS) and parallel imaging, is evaluated for the acceleration of CEST in brain and breast. METHODS: The CEST data were collected in phantoms, brain (N = 3), and breast (N = 2). Retrospective Cartesian undersampling was implemented and the reconstruction results of PBCS-CEST were compared with BCS-CEST and k-t sparse-SENSE CEST. The normalized RMSE and the high-frequency error norm were used for quantitative comparison. RESULTS: In phantom and in vivo brain experiments, the acceleration factor of R = 10 (24 k-space lines) was achieved and in breast R = 5 (30 k-space lines), without compromising the quality of the PBCS-reconstructed magnetization transfer rate asymmetry maps and Z-spectra. Parallel BCS provides better reconstruction quality when compared with BCS, k-t sparse-SENSE, and SENSE methods using the same number of samples. Parallel BCS overperforms BCS, indicating that the inclusion of coil sensitivity improves the reconstruction of the CEST data. CONCLUSION: The PBCS method accelerates CEST without compromising its quality. Compressed sensing in combination with parallel imaging can provide a valuable alternative to parallel imaging alone for accelerating CEST experiments.

Z-spectrum appearance and interpretation in the presence of fat: Influence of acquisition parameters.

PURPOSE: Chemical exchange saturation transfer (CEST) MRI is increasingly evolving from brain to body applications. One of the known problems in the body imaging is the presence of strong lipid signals. Although their influence on the CEST effect is acknowledged, there was no study that focuses on the interplay among echo time, fat fraction, and Z-spectrum. This study strives to address these points, with the emphasis on the application in the breast. METHODS: Z-spectra were simulated in phase and out of phase of the main fat peak at -3.4 ppm, with the fat fraction varying from 0 to 100%. The magnetization transfer ratio asymmetry in two ranges, centering at the exchanging pool and at 3.5 ppm approximately opposite the nonexchanging fat pool, were calculated and were plotted against fat fraction. The results were verified in phantoms and in vivo. RESULTS: The results demonstrate the combined influence of fat fraction and echo time on the Z-spectrum for gradient echo based CEST acquisitions. The influence is straightforward in the in-phase images, but it is more complicated in the out-of-phase images, potentially leading to erroneous CEST contrast. CONCLUSIONS: This study provides a basis for understanding the origin and appearance of lipid artifacts in CEST imaging, and lays the foundation for their efficient removal. Magn Reson Med 79:2731-2737, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Microstructural correlates of 3D steady-state inhomogeneous magnetization transfer (ihMT) in the human brain white matter assessed by myelin water imaging and diffusion tensor imaging.

PURPOSE: To compare the recently introduced inhomogeneous magnetization transfer (ihMT) technique with more established MRI techniques including myelin water imaging (MWI) and diffusion tensor imaging (DTI), and to evaluate the microstructural attributes correlating with this new contrast method in the human brain white matter. METHODS: Eight adult healthy volunteers underwent T1 -weighted, ihMT, MWI, and DTI imaging on a 3T human scanner. The ihMT ratio (ihMTR), myelin water fraction (MWF), fractional anisotropy (FA), radial diffusivity (RD), axial diffusivity (AD), and mean diffusivity (MD) values were calculated from different white matter tracts. The angle ( θ ) between the directions of the principal eigenvector, as measured by DTI, and the main magnetic field was calculated for all voxels from various fiber tracts. The ihMTR was correlated with MWF and DTI metrics. RESULTS: A strong correlation was found between ihMTR and MWF (ρ = 0.77, P < 0.0001). This was followed by moderate to weak correlations between ihMTR and DTI metrics: RD (ρ = -0.30, P < 0.0001), FA (ρ = 0.20, P < 0.0001), MD (ρ = -0.19, P < 0.0001), AD (ρ = 0.02, P < 0.0001). A strong correlation was found between ihMTR and θ (ρ = -0.541, P < 0.0001). CONCLUSION: The strong correlation with myelin water imaging and its low coefficient of variation suggest that ihMT has the potential to become a new structural imaging marker of myelin. The substantial orientational dependence of ihMT should be taken into account when evaluating and quantitatively interpreting ihMT results.

Frequency Offset Corrected Inversion Pulse for B0 and B1 Insensitive Fat Suppression at 3T: Application to MR Neurography of Brachial Plexus.

BACKGROUND: The 3D short tau inversion recovery (STIR) sequence is routinely used in clinical MRI to achieve robust fat suppression. However, the performance of the commonly used adiabatic inversion pulse, hyperbolic secant (HS), is compromised in challenging areas with increased B0 and B1 inhomogeneities, such as brachial plexus at 3T. PURPOSE: To demonstrate the frequency offset corrected inversion (FOCI) pulse as an efficient fat suppression STIR pulse with increased robustness to B0 and B1 inhomogeneities at 3T, compared to the HS pulse. STUDY TYPE: Prospective. SUBJECTS/PHANTOM: Initial evaluation was performed in phantoms and one healthy volunteer by varying the B1 field, while subsequent comparison was performed in three healthy volunteers and five patients without varying the B1 . FIELD STRENGTH/SEQUENCE: 3T; 3D TSE-STIR with HS and FOCI pulses. ASSESSMENT: Brachial plexus images were qualitatively evaluated by two musculoskeletal radiologists independently using a four-point grading scale for fat suppression, shading artifacts, and nerve visualization. STATISTICAL TEST: The Wilcoxon signed-rank test with P < 0.05 was considered statistically significant. RESULTS: Simulations and phantom experiments demonstrated broader bandwidth (2.5 kHz vs. 0.83 kHz, increased B0 robustness) at the same adiabatic threshold and lower adiabatic threshold (5 µT vs. 7 µT at 3.5 ppm, increased B1 robustness) at the same bandwidth with the FOCI pulse compared to the HS pulse With increased bandwidth, the FOCI pulse achieved robust fat suppression even at 50% of maximum B1 strength, while the HS pulse required >75% of maximum B1 strength. Compared to the standard 3D TSE-STIR with HS pulse, the FOCI pulse achieved uniform fat suppression (P < 0.05), better nerve visualization (P < 0.05), and minimal shading artifacts (P < 0.01) in brachial plexus at 3T. DATA CONCLUSION: The FOCI pulse has increased robustness to B0 and B1 inhomogeneities, compared to the HS pulse, and enables uniform fat suppression in brachial plexus at 3T. LEVEL OF EVIDENCE: 1 Techinical Efficacy: Stage 1 J. Magn. Reson. Imaging 2018;48:1104-1111.

Proteochemometrics-Based Prediction of Peptide Binding to HLA-DP Proteins.

Human leukocyte antigens (HLA) class II proteins are involved in the antigen processing in the antigen presenting cells. They form complexes with antigen peptide fragments. The peptide-HLA protein complexes are presented on the cell surface where they are recognized by helper T cells (Th cells). HLA-DP is one of the three HLA class II loci. The HLA-DP proteins are associated with a significant number of autoimmune diseases, as well as with a susceptibility or resistance to a number of infectious agents. In the present study, we apply proteochemometrics-a method for bioactivity modeling of multiple ligands binding to multiple target proteins-to derive and validate a robust model for peptide binding prediction to the 7 most frequent HLA-DP proteins. The model is able to identify 86% of the binders in the top 10% of the best predicted nonamers generated from one protein.