Structure-based mapping of the histone-binding pocket of KDM4D using functionalized tetrazole and pyridine core compounds.

KDM4 histone demethylases became an exciting target for inhibitor development as the evidence linking them directly to tumorigenesis mounts. In this study, we set out to better understand the binding cavity using an X-ray crystallographic approach to provide a detailed landscape of possible interactions within the under-investigated region of KDM4. Our design strategy was based on utilizing known KDM binding motifs, such as nicotinic acid and tetrazolylhydrazides, as core motifs that we decided to enrich with flexible tails to map the distal histone binding site. The resulting X-ray structures of the novel compounds bound to KDM4D, a representative of the KDM4 family, revealed the interaction pattern with distal residues in the histone-binding site. The most prominent protein rearrangement detected upon ligand binding is the loop movement that blocks the accessibility to the histone binding site. Apart from providing new sites that potential inhibitors can target, the novel compounds may prove helpful in exploring the capacity of ligands to bind in sites distal to the cofactor-binding site of other KDMs or 2-oxoglutarate (2OG)-dependent oxygenases. The case study proves that combining a strong small binding motif with flexible tails to probe the binding pocket will facilitate lead discovery in classical drug-discovery campaigns, given the ease of accessing X-ray quality crystals.

Fine-Grained Permeable Surface Mapping through Parallel U-Net.

Permeable surface mapping, which mainly is the identification of surface materials that will percolate, is essential for various environmental and civil engineering applications, such as urban planning, stormwater management, and groundwater modeling. Traditionally, this task involves labor-intensive manual classification, but deep learning offers an efficient alternative. Although several studies have tackled aerial image segmentation, the challenges in permeable surface mapping arid environments remain largely unexplored because of the difficulties in distinguishing pixel values of the input data and due to the unbalanced distribution of its classes. To address these issues, this research introduces a novel approach using a parallel U-Net model for the fine-grained semantic segmentation of permeable surfaces. The process involves binary classification to distinguish between entirely and partially permeable surfaces, followed by fine-grained classification into four distinct permeability levels. Results show that this novel method enhances accuracy, particularly when working with small, unbalanced datasets dominated by a single category. Furthermore, the proposed model is capable of generalizing across different geographical domains. Domain adaptation is explored to transfer knowledge from one location to another, addressing the challenges posed by varying environmental characteristics. Experiments demonstrate that the parallel U-Net model outperforms the baseline methods when applied across domains. To support this research and inspire future research, a novel permeable surface dataset is introduced, with pixel-wise fine-grained labeling for five distinct permeable surface classes. In summary, in this work, we offer a novel solution to permeable surface mapping, extend the boundaries of arid environment mapping, introduce a large-scale permeable surface dataset, and explore cross-area applications of the proposed model. The three contributions are enhancing the efficiency and accuracy of permeable surface mapping while progressing in this field.

Regional conduction velocities determined by noninvasive mapping are associated with arrhythmia-free survival after atrial fibrillation ablation.

BACKGROUND: Atrial arrhythmogenic substrate is a key determinant of atrial fibrillation (AF) recurrence after pulmonary vein isolation (PVI), and reduced conduction velocities have been linked to adverse outcome. However, a noninvasive method to assess such electrophysiologic substrate is not available to date. OBJECTIVE: This study aimed to noninvasively assess regional conduction velocities and their association with arrhythmia-free survival after PVI. METHODS: A consecutive 52 patients scheduled for AF ablation (PVI only) and 19 healthy controls were prospectively included and received electrocardiographic imaging (ECGi) to noninvasively determine regional atrial conduction velocities in sinus rhythm. A novel ECGi technology obviating the need of additional computed tomography or cardiac magnetic resonance imaging was applied and validated by invasive mapping. RESULTS: Mean ECGi-determined atrial conduction velocities were significantly lower in AF patients than in healthy controls (1.45 ± 0.15 m/s vs 1.64 ± 0.15 m/s; P < .0001). Differences were particularly pronounced in a regional analysis considering only the segment with the lowest average conduction velocity in each patient (0.8 ± 0.22 m/s vs 1.08 ± 0.26 m/s; P < .0001). This average conduction velocity of the "slowest" segment was independently associated with arrhythmia recurrence and better discriminated between PVI responders and nonresponders than previously proposed predictors, including left atrial size and late gadolinium enhancement (magnetic resonance imaging). Patients without slow-conduction areas (mean conduction velocity <0.78 m/s) showed significantly higher 12-month arrhythmia-free survival than those with 1 or more slow-conduction areas (88.9% vs 48.0%; P = .002). CONCLUSION: This is the first study to investigate regional atrial conduction velocities noninvasively. The absence of ECGi-determined slow-conduction areas well discriminates PVI responders from nonresponders. Such noninvasive assessment of electrical arrhythmogenic substrate may guide treatment strategies and be a step toward personalized AF therapy.

Quantum oscillations evidence for topological bands in kagome metal ScV6Sn6.

Metals with kagome lattice provide bulk materials to host both the flat-band and Dirac electronic dispersions. A new family of kagome metals is recently discovered inAV6Sn6. The Dirac electronic structures of this material needs more experimental evidence to confirm. In the manuscript, we investigate this problem by resolving the quantum oscillations in both electrical transport and magnetization in ScV6Sn6. The revealed orbits are consistent with the electronic band structure models. Furthermore, the Berry phase of a dominating orbit is revealed to be aroundπ, providing direct evidence for the topological band structure, which is consistent with calculations. Our results demonstrate a rich physics and shed light on the correlated topological ground state of this kagome metal.

Phase Quantification of Heterogeneous Surfaces Using DFT-Simulated Valence Band Photoemission Spectra.

Quantifying the crystallographic phases present at a surface is an important challenge in fields such as functional materials and surface science. X-ray photoelectron spectroscopy (XPS) is routinely employed in surface characterization to identify and quantify chemical species through core line analysis. Valence band (VB) spectra contain characteristic but complex features that provide information on the electronic density of states (DoS) and thus can be understood theoretically using density functional theory (DFT). Here, we present a method of fitting experimental photoemission spectra with DFT models for quantitative analysis of heterogeneous systems, specifically mapping the anatase to rutile ratio across the surface of mixed-phase TiO2 thin films. The results were correlated with mapped photocatalytic activity measured using a resazurin-based smart ink. This method allows large-scale functional and surface composition mapping in heterogeneous systems and demonstrates the unique insights gained from DFT-simulated spectra on the electronic structure origins of complex VB spectral features.

Real-Time Stereo-Based Ocean Surface Mapping for Robotic Floating Platforms: Concept and Methodology.

Consider the case of a small, unmanned boat that is performing an autonomous mission. Naturally, such a platform might need to approximate the ocean surface of its surroundings in real-time. Much like obstacle mapping in autonomous (off-road) rovers, an approximation of the ocean surface in a vessel's surroundings in real-time can be used for improved control and optimized route planning. Unfortunately, such an approximation seems to require either expensive and heavy sensors or external logistics that are mostly not available for small or low-cost vessels. In this paper, we present a real-time method for detecting and tracking ocean waves around a floating object that is based on stereo vision sensors. Based on a large set of experiments, we conclude that the presented method allows reliable, real-time, and cost-effective ocean surface mapping suitable for small autonomous boats.

Comparison of Dry and Wet Electrodes for Detecting Gastrointestinal Activity Patterns from Body Surface Electrical Recordings.

Gastrointestinal motility patterns can be mapped via electrical signals measured non-invasively on the body surface. However, short-term (≈ 2-4 h) meal response studies as well as long-term monitoring (≥ 24 h) may be hindered by skin irritation inherent with traditional Ag/AgCl pre-gelled ("wet") electrodes. The aim of this work was to investigate the practical utility of using dry electrodes for GI body-surface electrical measurements. To directly compare dry vs. wet electrodes, we simultaneously recorded electrical signals from both types arranged in a 9-electrode array during an ≈ 2.5 h colonic meal-response study. Wavelet-based analyses were used to identify the signature post-meal colonic cyclic motor patterns. Blinded comparison of signal quality was carried out by four expert manual reviewers in order to assess the practical utility of each electrode type for identifying GI activity patterns. Dry electrodes recorded high-quality GI signals with signal-to-noise ratio of 10.0 ± 3.5 dB, comparable to that of wet electrodes (9.9 ± 3.6 dB). Although users rated dry electrodes as slightly more difficult to self-apply, they caused no skin irritation and were thus better tolerated overall. Dry electrodes are a more comfortable alternative to conventional wet electrode systems, and may offer a potentially viable option for long-term GI monitoring studies.

Ultra-high-resolution Mapping of Cortical Layers 3T-Guided 7T MRI.

7T MRI provides unprecedented resolution for examining human brain anatomy in vivo. For example, 7T MRI enables deep thickness measurement of laminar subdivisions in the right fusiform area. Existing laminar thickness measurement on 7T is labor intensive, and error prone since the visual inspection of the image is typically along one of the three orthogonal planes (axial, coronal, or sagittal view). To overcome this, we propose a new analytics tool that allows flexible quantification of cortical thickness on a 2D plane that is orthogonal to the cortical surface (beyond axial, coronal, and sagittal views) based on the 3D computational surface reconstruction. The proposed method further distinguishes high quality 2D planes and the low-quality ones by automatically inspecting the angles between the surface normals and slice direction. In our approach, we acquired a pair of 3T and 7T scans (same subject). We extracted the brain surfaces from the 3T scan using MaCRUISE and projected the surface to the 7T scan's space. After computing the angles between the surface normals and axial direction vector, we found that 18.58% of surface points were angled at more than 80° with the axial direction vector and had 2D axial planes with visually distinguishable cortical layers. 15.12% of the surface points with normal vectors angled at 30° or lesser with the axial direction, had poor 2D axial slices for visual inspection of the cortical layers. This effort promises to dramatically extend the area of cortex that can be quantified with ultra-high resolution in-plane imaging methods.

Detailed comparative analysis of environmental microparticle deposition characteristics between human and monkey nasal cavities using a surface mapping technique.

Inhaled particulate matter is associated with nasal diseases such as allergic rhinitis, rhinosinusitis and neural disorders. Its health risks on humans are usually evaluated by measurements on monkeys as they share close phylogenetic relationship. However, the reliability of cross-species toxicological extrapolation is in doubt due to physiological and anatomical variations, which greatly undermine the reliability of these expensive human surrogate models. This study numerically investigated in-depth microparticle transport and deposition characteristics on human and monkey (Macaca fuscata) nasal cavities that were reconstructed from CT-images. Deposition characteristics of 1-30µm particles were investigated under resting and active breathing conditions. Similar trends were observed for total deposition efficiencies and a single correlation using Stokes Number was fitted for both species and both breathing conditions, which is convenient for monkey-human extrapolation. Regional deposition patterns were carefully compared using the surface mapping technique. Deposition patterns of low, medium and high inertial particles, classified based on their total deposition efficiencies, were further analyzed in the 3D view and the mapped 2D view, which allows locating particle depositions on specific nasal regions. According to the particle intensity contours and regional deposition profiles, the major differences were observed at the vestibule and the floor of the nasal cavity, where higher deposition intensities of medium and high inertial particles were shown in the monkey case than the human case. Comparisons of airflow streamlines indicated that the cross-species variations of microparticle deposition patterns are mainly contributed by two factors. First, the more oblique directions of monkey nostrils result in a sharper airflow turn in the vestibule region. Second, the monkey's relatively narrower nasal valves lead to higher impaction of medium and high inertial particles on the nasal cavity floor. The methods and findings in this study would contribute to an improved cross-species toxicological extrapolation between human and monkey nasal cavities.

Validation of noninvasive body-surface gastric mapping for detecting gastric slow-wave spatiotemporal features by simultaneous serosal mapping in porcine.

Gastric disorders are increasingly prevalent, but reliable noninvasive tools to objectively assess gastric function are lacking. Body-surface gastric mapping (BSGM) is a noninvasive method for the detection of gastric electrophysiological features, which are correlated with symptoms in patients with gastroparesis and functional dyspepsia. Previous studies have validated the relationship between serosal and cutaneous recordings from limited number of channels. This study aimed to comprehensively evaluate the basis of BSGM from 64 cutaneous channels and reliably identify spatial biomarkers associated with slow-wave dysrhythmias. High-resolution electrode arrays were placed to simultaneously capture slow waves from the gastric serosa (32 × 6 electrodes at 4 mm spacing) and epigastrium (8 × 8 electrodes at 20 mm spacing) in 14 porcine subjects. BSGM signals were processed based on a combination of wavelet and phase information analyses. A total of 1,185 individual cycles of slow waves were assessed, out of which 897 (76%) were classified as normal antegrade waves, occurring in 10 (71%) subjects studied. BSGM accurately detected the underlying slow wave in terms of frequency (r = 0.99, P = 0.43) as well as the direction of propagation (P = 0.41, F-measure: 0.92). In addition, the cycle-by-cycle match between BSGM and transitions of gastric slow wave dysrhythmias was demonstrated. These results validate BSGM as a suitable method for noninvasively and accurately detecting gastric slow-wave spatiotemporal profiles from the body surface.NEW & NOTEWORTHY Gastric dysfunctions are associated with abnormalities in the gastric bioelectrical slow waves. Noninvasive detection of gastric slow waves from the body surface can be achieved through multichannel, high-resolution, body-surface gastric mapping (BSGM). BSGM matched the spatiotemporal characteristics of gastric slow waves recorded directly and simultaneously from the serosal surface of the stomach. Abnormal gastric slow waves, such as retrograde propagation, ectopic pacemaker, and colliding wavefronts can be detected by changes in the phase of BSGM.

Geometric effects of volume-to-surface mapping of fMRI data.

In this work, we identify a problem with the process of volume-to-surface mapping of functional Magnetic Resonance Imaging (fMRI) data that emerges in local connectivity analysis. We show that neighborhood correlations on the surface of the brain vary spatially with the gyral structure, even when the underlying volumetric data are uncorrelated noise. This could potentially have impacted studies focusing upon local neighborhood connectivity. We explore the effects of this anomaly across varying data resolutions and surface mesh densities, and propose several measures to mitigate these unwanted effects.

Thalamic Shape Abnormalities Differentially Relate to Cognitive Performance in Early-Onset and Adult-Onset Schizophrenia.

Early-onset schizophrenia (EOS) shares many biological and clinical features with adult-onset schizophrenia (AOS), but may represent a unique subgroup with greater susceptibility for disease onset and worsened symptomatology and progression, which could potentially derive from exaggerated neurodevelopmental abnormalities. Neurobiological explanations of schizophrenia have emphasized the involvement of deep-brain structures, particularly alterations of the thalamus, which have been linked to core features of the disorder. The aim of this study was to compare thalamic shape abnormalities between EOS and AOS subjects and determine whether unique behavioral profiles related to these differences. It was hypothesized abnormal thalamic shape would be observed in anterior, mediodorsal and pulvinar regions in both schizophrenia groups relative to control subjects, but exacerbated in EOS. Magnetic resonance T1-weighted images were collected from adult individuals with EOS (n = 28), AOS (n = 33), and healthy control subjects (n = 60), as well as collection of clinical and cognitive measures. Large deformation high-dimensional brain mapping was used to obtain three-dimensional surfaces of the thalamus. General linear models were used to compare groups on surface shape features, and Pearson correlations were used to examine relationships between thalamic shape and behavioral measures. Results revealed both EOS and AOS groups demonstrated significant abnormal shape of anterior, lateral and pulvinar thalamic regions relative to CON (all p < 0.007). Relative to AOS, EOS exhibited exacerbated abnormalities in posterior lateral, mediodorsal and lateral geniculate thalamic regions (p = 0.003). Thalamic abnormalities related to worse episodic memory in EOS (p = 0.03) and worse working memory (p = 0.047) and executive functioning (p = 0003) in AOS. Overall, findings suggest thalamic abnormalities are a prominent feature in both early- and late-onset schizophrenia, but exaggerated in EOS and have different brain-behavior profiles for each. The persistence of these abnormalities in adult EOS patients suggests they may represent markers of disrupted neurodevelopment that uniquely relate to the clinical and cognitive aspects of the illness.

Repolarization abnormalities unmasked with a 252-lead BSM system in patients with ARVC and healthy gene carriers.

BACKGROUND: Diagnosing arrhythmogenic right ventricular cardiomyopathy (ARVC) at an early stage can be challenging even after ECG recording and a combination of several imaging techniques. The purpose of this study was to explore if a body surface mapping (BSM) system with 252-leads could identify repolarization abnormalities and thereby diagnose early stages of ARVC. METHODS: ARVC patients, gene carriers without signs of ARVC and controls underwent a 12-lead resting ECG, signal-averaged ECG, echocardiography, 24-hours Holter monitoring, and BSM with electrocardiographic imaging (ECGI). All 252-leads, divided into four quadrants of the vest, were analyzed regarding concordances between T wave polarity and QRS main vector. RESULTS: Of 40 patients included there were 12 ARVC patients, 20 gene carriers, and 8 controls. The ARVC patients had two different repolarization patterns, one with more pronounced negative T waves at the lower left panel and another with mixed changes that clearly differed from the controls, all of whom had a normal 12 lead ECGs and consistent repolarization patterns on their BSM recordings. The patterns observed in ARVC patients were also present in 5/20 (25%) gene carriers, three of whom had normal resting ECG. A novel repolarization index successfully detected all ARVC patients and 88% of gene carriers with pathologic repolarization pattern. CONCLUSIONS: The finding that abnormal repolarization patterns could be unmasked by BSM in 25% of healthy gene carriers, suggests that it may potentially be a useful tool for identifying early manifestations of ARVC. Further and larger studies are warranted to assess its diagnostic accuracy.

G-RMOS: GPU-accelerated Riemannian Metric Optimization on Surfaces.

Surface mapping is used in various brain imaging studies, such as for mapping gray matter atrophy patterns in Alzheimer's disease. Riemannian metrics on surface (RMOS) is a state-of-the-art surface mapping algorithm that optimizes Riemannian metrics to establish one-to-one correspondences between surfaces in the Laplace-Beltrami embedding space. However, owing to the complex calculation with accurate one-to-one correspondences, RMOS registration takes a long time. In this study, we propose G-RMOS, a graphics processing unit (GPU)-accelerated RMOS registration pipeline that uses three GPU kernel design strategies: 1. using GPU computing capability with a batch scheme; 2. using the cache in the GPU block to minimize memory latency in register and shared memory; and 3. maximizing the effective number of instructions per GPU cycle using instruction level parallelism. Using the experimental results, we compare the acceleration speed of the G-RMOS framework with that of RMOS using hippocampus and cortical surfaces, and show that G-RMOS achieves a significant speedup in surface mapping. We also compare the memory requirements for cortical surface mapping and show that G-RMOS uses less memory than RMOS.

Noninvasive electrocardiographic assessment of ventricular activation and remodeling response to cardiac resynchronization therapy.

BACKGROUND: Cardiac resynchronization therapy (CRT) produces acute changes in electric resynchronization that can be measured noninvasively with electrocardiographic body surface mapping (ECGi). The relation between baseline acute electrophysiology metrics and their manipulation with CRT and reverse remodeling is unclear. OBJECTIVE: To test (ECGi) derived parameters of electrical activation as predictors of volumetric response to CRT. METHODS: ECGi was performed in 21 patients directly following CRT implant. Activation parameters (left ventricular total activation time [LVtat], global biventricular total activation time [VVtat], global left/right ventricular electrical synchrony [VVsync], and global left ventricular dispersion of activation times [LVdisp]) were measured at baseline and following echocardiographically optimized CRT. Remodeling response (>15% reduction left ventricular end-systolic volume) was assessed 6 months post CRT. RESULTS: Patients were aged 68.9 ± 12.1 years, 81% were male, and 57% were ischemic. Baseline measures of dyssynchrony were more pronounced in left bundle branch block (LBBB) vs non-LBBB. ECGi demonstrated a trend of greater interventricular dyssynchrony between responders and nonresponders that did not reach statistical significance (VVsync: -45.7 ± 22.4 ms vs -25.1 ± 29.3 ms, P = .227). Remaining activation parameters were similar between responders and nonresponders (VVtat 101 ± 22.0 ms vs 98.9 ± 23.4 ms, P = .838; LVtat 86.4 ± 17.1 ms vs 85.1 ± 27.7 ms, P = .904; LVdisp 28.2 ± 6.3 ms vs 27.0 ± 8.7 ms, P = .726). In volumetric responders activation parameters were significantly improved with CRT compared to nonresponders: VV sync (-45.67 ± 22.41 ms vs 2.33±18.87 ms, P = .001), VVtat (101 ± 22.04 ms vs 71 ± 14.01 ms, P = .002), LVtat (86.44 ± 17.15 ms vs 67.67 ± 11.31 ms, P = .006), and LVdisp (28.22 ± 6.3 ms vs 21.56 ± 4.45 ms, P = .008). CONCLUSION: Baseline ECGi activation times did not predict CRT volumetric response. Volumetric responders exhibited significant improvements in ECGi-derived metrics with CRT. ECGi does not select CRT candidates but may be a useful adjunct to guide left ventricle lead implants and to perform postimplant CRT optimization.

The differential solvent exposure of N-terminal residues provides "fingerprints" of alpha-synuclein fibrillar polymorphs.

Synucleinopathies are neurodegenerative diseases characterized by the presence of intracellular deposits containing the protein alpha-synuclein (aSYN) within patients' brains. It has been shown that aSYN can form structurally distinct fibrillar assemblies, also termed polymorphs. We previously showed that distinct aSYN polymorphs assembled in vitro, named fibrils, ribbons, and fibrils 91, differentially bind to and seed the aggregation of endogenous aSYN in neuronal cells, which suggests that distinct synucleinopathies may arise from aSYN polymorphs. In order to better understand the differential interactions of aSYN polymorphs with their partner proteins, we mapped aSYN polymorphs surfaces. We used limited proteolysis, hydrogen-deuterium exchange, and differential antibody accessibility to identify amino acids on their surfaces. We showed that the aSYN C-terminal region spanning residues 94 to 140 exhibited similarly high solvent accessibility in these three polymorphs. However, the N-terminal amino acid residues 1 to 38 of fibrils were exposed to the solvent, while only residues 1 to 18 within fibrils 91 were exposed, and no N-terminal residues within ribbons were solvent-exposed. It is likely that these differences in surface accessibility contribute to the differential binding of distinct aSYN polymorphs to partner proteins. We thus posit that the polypeptides exposed on the surface of distinct aSYN fibrillar polymorphs are comparable to fingerprints. Our findings have diagnostic and therapeutic potential, particularly in the prion-like propagation of fibrillar aSYN, as they can facilitate the design of ligands that specifically bind and distinguish between fibrillar polymorphs.

Protein Footprinting via Covalent Protein Painting Reveals Structural Changes of the Proteome in Alzheimer's Disease.

Misfolding and aggregation of amyloid-ß peptide and hyperphosphorylated tau are molecular markers of Alzheimer's disease (AD), and although the 3D structures of these aberrantly folded proteins have been visualized in exquisite detail, no method has been able to survey protein folding across the proteome in AD. Here, we present covalent protein painting (CPP), a mass spectrometry-based protein footprinting approach to quantify the accessibility of lysine ε-amines for covalent modification at the surface of natively folded proteins. We used CPP to survey the reactivity of 2645 lysine residues and therewith the structural proteome of HEK293T cells and found that reactivity increased upon mild heat shock. CPP revealed that the accessibility of lysine residues for covalent modification in tubulin-ß (TUBB), in succinate dehydrogenase (SHDB), and in amyloid-ß peptide (Aß) is altered in human postmortem brain samples of patients with neurodegenerative diseases. The structural alterations of TUBB and SHDB in patients with AD, dementia with Lewy bodies (DLB), or both point to broader perturbations of the 3D proteome beyond Aß and hyperphosphorylated tau.

Body Surface Potential Mapping: Contemporary Applications and Future Perspectives.

Body surface potential mapping (BSPM) is a noninvasive modality to assess cardiac bioelectric activity with a rich history of practical applications for both research and clinical investigation. BSPM provides comprehensive acquisition of bioelectric signals across the entire thorax, allowing for more complex and extensive analysis than the standard electrocardiogram (ECG). Despite its advantages, BSPM is not a common clinical tool. BSPM does, however, serve as a valuable research tool and as an input for other modes of analysis such as electrocardiographic imaging and, more recently, machine learning and artificial intelligence. In this report, we examine contemporary uses of BSPM, and provide an assessment of its future prospects in both clinical and research environments. We assess the state of the art of BSPM implementations and explore modern applications of advanced modeling and statistical analysis of BSPM data. We predict that BSPM will continue to be a valuable research tool, and will find clinical utility at the intersection of computational modeling approaches and artificial intelligence.