Search Results (430)

Background/Objectives: This study identifies novel dihydroorotate dehydrogenase (DHODH) inhibitors exhibiting potent broad-spectrum antiviral agents, particularly against influenza A virus (A/PR/8/34(H1N1)) and SARS-CoV-2. Methods: Structure-based virtual screening of 1.6 million compounds (ChemDiv and TargetMol databases) yielded 10 candidates, with compounds 6, 9, and 10 demonstrating significant anti-influenza activity (IC₅₀ = 4.85 ± 0.58, 7.35 ± 1.65, and 1.75 ± 0.28 μM, respectively). Building on these, molecular hybridization principles and scaffold hopping principles were applied to design and synthesize six novel compounds (11–16) through cyclization, coupling, and carboxylate deprotection. Prior to subsequent biological assays, the molecular structures of each compound were elucidated by NMR spectroscopy and MS. Their antiviral activities were subsequently assessed against both influenza virus and SARS-CoV-2. The compound 11, demonstrating the most potent antiviral activity, was further subjected to surface plasmon resonance (SPR) analysis to assess its binding affinity for human DHODH. Results: Compound 11 emerged as the most potent DHODH inhibitor (K_D = 6.06 μM), exhibiting superior broad-spectrum antiviral activities (IC₅₀ = 0.85 ± 0.05 μM, A/PR/8/34(H1N1); IC₅₀ = 3.60 ± 0.67 μM, SARS-CoV-2) to the reported DHODH inhibitor (Teriflunomide, IC₅₀ = 35.02 ± 3.33 μM, A/PR/8/34(H1N1); IC₅₀ = 26.06 ± 4.32 μM, SARS-CoV-2). Mechanistic evaluations via 100 ns MD simulations and QM/MM calculations revealed stable binding interactions, particularly hydrogen bonds with GLN47 and ARG136, while alanine scanning mutagenesis confirmed these residues’ critical roles in binding stability. Conclusions: This work identifies compound 11 as a potent broad-spectrum antiviral compound, offering a promising strategy for broad-spectrum antiviral therapy against RNA viruses by depleting pyrimidine pools essential for viral replication. Full article

Understanding the atomistic basis of multi-layer mechanisms employed by broadly reactive neutralizing antibodies of the SARS-CoV-2 spike protein without directly blocking receptor engagement remains an important challenge in coronavirus immunology. Class 4 antibodies represent an intriguing case: they target a deeply conserved, cryptic epitope on the receptor-binding domain yet exhibit variable neutralization potency across subgroups F1 (CR3022, EY6A, COVA1-16), F2 (DH1047), and F3 (S2X259). The molecular basis for this variability is not fully understood. Here, we employed a multi-modal computational approach integrating atomistic and coarse-grained molecular dynamics simulations, binding free energy calculations, mutational scanning, and dynamic network analysis to elucidate how these antibodies engage the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein and influence its function. Our results reveal that neutralization efficacy arises from the interplay of direct interfacial interactions and allosteric effects. Group F1 antibodies (CR3022, EY6A, COVA1-16) primarily operate via classic allostery, modulating flexibility in RBD loop regions to indirectly interfere with the ACE2 receptor binding through long-range effects. Group F2 antibody DH1047 represents an intermediate mechanism, combining partial steric hindrance—through engagement of ACE2-critical residues T376, R408, V503, and Y508—with significant allosteric influence, facilitated by localized communication pathways linking the epitope to the receptor interface. Group F3 antibody S2X259 achieves potent neutralization through a synergistic mechanism involving direct competition with ACE2 and localized allosteric stabilization, albeit with potentially increased escape vulnerability. Dynamic network analysis identified a conserved “allosteric ring” within the RBD core that serves as a structural scaffold for long-range signal propagation, with antibody-specific extensions modulating communication to the ACE2 interface. These findings support a model where Class 4 neutralization strategies evolve through the refinement of peripheral allosteric connections rather than epitope redesign. This study establishes a robust computational framework for understanding the atomistic basis of neutralization activity and immune escape for Class 4 antibodies, highlighting how the interplay of binding energetics, conformational dynamics, and allosteric modulation governs their effectiveness against SARS-CoV-2. Full article

Reliable sea ice extent (SIE) information is essential for Arctic navigation, climate research, and resource exploration. Synthetic Aperture Radar (SAR), with its all-weather, high-resolution capabilities, is well suited for SIE extraction. This study evaluates a pan-Arctic SIE product automatically generated from over 85,000 Sentinel-1 SAR images acquired between 2020 and 2023 using an integrated stacking U-Net framework. To validate its performance, all the SIE products are converted to sea ice concentration (SIC) and compared against the 3.125 km resolution Advanced Microwave Scanning Radiometer-2 (AMSR2) SIC products. The S1-derived SIC shows strong agreement with AMSR2 SIC, yielding a Pearson correlation of 0.99 and annual mean absolute differences between 5.93% and 7.85%. Case analyses demonstrate that the S1 products effectively capture small-scale ice features, such as floes, which are often missed by AMSR2. Furthermore, we introduce an Integrated Index to quantify the relative contribution of each sub-model within the integrated stacking U-Net framework. The analysis indicates that three sub-models provide the primary contribution to the ensemble, offering insights into improving integration efficiency and guiding the design of more scientifically grounded ensemble strategies. Full article

To directly address the important issue of MRI geometric distortions in stereotactic radiosurgery (SRS) planning, we performed a phantom study of sequence acquisition optimization. This study analyzed, in particular, the effects of clinically relevant gadolinium (Gd) concentration as filling solution for the phantom, as well as phase encoding reversal direction and flip angle on distortion. We created a rigid geometric grid phantom with 840 fiducial markers for distortion quantification on a 3T MRI scanner. To choose the optimal filling solution, an anthropomorphic RANDO phantom was employed, and 1 mmol/L gadolinium was chosen due to clinical relevance. An automated Python-based software (version 3.7.1) was developed for efficient detection and matching of phantom inserts between MRI and CT scans. A series of MRI acquisition parameter optimizations were systematically evaluated. The standard SRS protocol exhibited the highest average distortion of 1.301 mm. Notably, reversing the phase-encoding direction to anterior–posterior (AP) reduced the mean distortion to 0.725 mm, a 44.27% decrease, while the maximum distortion was reduced by 15.65%. The AP phase sequence maintained acquisition time, SAR, SNR, and CNR within acceptable limits. Additional distortion reduction was achieved by increasing the flip angle from 12° to 18°. In this work, we succeeded in significantly reducing the mean distortion observed in phantom images. As the gadolinium concentration used in the phantom is clinically similar to the gadolinium concentration observed in patients undergoing MRI scans with contrast agents, the achieved distortion reduction is prospectively reproducible in patients. Full article

The COVID-19 pandemic caused by SARS-CoV-2 has significantly impacted public health worldwide. This study aimed to assess the clinical and diagnostic features of COVID-19 cases in the Tlemcen region, Algeria, and analyze epidemiological trends from January to December 2021. This retrospective study included 68,745 confirmed snapshot active COVID-19 cases from the Public Local Health Care Establishment (EPSP)—University Hospital of Tlemcen. Patients underwent PCR testing and chest CT imaging for clinical evaluation. Data on symptoms, PCR cycle threshold (Ct) values, and CT imaging findings were collected, and statistical analysis was performed to examine the patient’s viral load and lung involvement data. Among 488 confirmed cases, common symptoms included fever, cough, and shortness of breath. PCR Ct values ranged from 15 to 35, and CT imaging revealed widespread lung involvement, with ground-glass opacities being the predominant feature. Epidemiological trends showed a consistent increase in cumulative cases, highlighting sustained transmission throughout the study period. Over the study period, epidemiological surveillance recorded a progressive rise in daily cases, peaking in July with 72 cases, followed by a gradual decline toward the end of the year. The findings underscore the utility of PCR Ct values and CT imaging in evaluating disease severity and monitoring regional case progression. The upward trend in cumulative cases emphasizes the need for ongoing public health measures and diagnostic strategies to manage future outbreaks effectively. Full article

Influenza A viruses that cause pandemics, as well as other harmful pathogens (e.g., SARS-CoV-2 variants), are known as the ‘silent bioterrorists’ of the 21st century. Due to high mutability, anti-influenza chemotherapeutic treatment is a vital defense strategy to combat both seasonal and pandemic influenza strains, especially when vaccines fail. Consequently, the development of novel therapies to combat this serious threat is of great concern. Hence, in this study, 3-(2-thienyl) acrylic acid (TA) was converted into amides of anti-influenza drugs (aminoadamantanes and oseltamivir) through TBTU-mediated coupling. The crystal structures of the thienyl-based amide hybrids (TA-Am (1), TA-Rim (2), TA-Os-OEt (3), and TA-OsC (4)) were also investigated using single-crystal X-ray diffraction, powder X-ray diffraction (PXRD), and differential scanning calorimetry (DSC). Moreover, the antiviral activities of the hybrids against influenza virus A/Fort Monmouth/1/1947 (H1N1), clinically isolated influenza strain A/Wuhan/359/1995 (H3N2), and oseltamivir-resistant A/Jinnan/15/2009 (H1N1) were evaluated in vitro. Amongst the tested thienyl-based amides, bisamide 8 (Boc-Os-Hda-TA) exhibited the most potent activity against influenza virus A (A/Wuhan/359/1995) with an IC₅₀ value of 18.52 μg/mL and a selectivity index (SI) = 13.0. Full article

The rapid evolution of SARS-CoV-2 has underscored the need for a detailed understanding of antibody binding mechanisms to combat immune evasion by emerging variants. In this study, we investigated the interactions between Class I neutralizing antibodies—BD55-1205, BD-604, OMI-42, P5S-1H1, and P5S-2B10—and the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein using multiscale modeling, which combined molecular simulations with the ensemble-based mutational scanning of the binding interfaces and binding free energy computations. A central theme emerging from this work is that the unique binding strength and resilience to immune escape of the BD55-1205 antibody are determined by leveraging a broad epitope footprint and distributed hotspot architecture, additionally supported by backbone-mediated specific interactions, which are less sensitive to amino acid substitutions and together enable exceptional tolerance to mutational escape. In contrast, BD-604 and OMI-42 exhibit localized binding modes with strong dependence on side-chain interactions, rendering them particularly vulnerable to escape mutations at K417N, L455M, F456L and A475V. Similarly, P5S-1H1 and P5S-2B10 display intermediate behavior—effective in some contexts but increasingly susceptible to antigenic drift due to narrower epitope coverage and concentrated hotspots. Our computational predictions show strong agreement with experimental deep mutational scanning data, validating the accuracy of the models and reinforcing the value of binding hotspot mapping in predicting antibody vulnerability. This work highlights that neutralization breadth and durability are not solely dictated by epitope location, but also by how binding energy is distributed across the interface. The results provide atomistic insight into mechanisms driving resilience to immune escape for broadly neutralizing antibodies targeting the ACE2 binding interface—which stems from cumulative effects of structural diversity in binding contacts, redundancy in interaction patterns and reduced vulnerability to mutation-prone positions. Full article

Background/Objectives: Airborne viral diseases pose a health risk, due to which there is a growing interest in developing filter materials capable of capturing fine particles containing virions from the air and that also have a virucidal effect. Nanofiber membranes made of poly(vinylidene fluoride) dissolved in N,N-dimethylacetamide and functionalized with copper, silver, and zinc nanoclusters were fabricated via electrospinning. This study aims to evaluate and compare the virucidal effects of nanofibers functionalized with metal nanoclusters against the human influenza A virus A/WSN/1933 (H1N1) and SARS-CoV-2. Methods: A comprehensive characterization of materials, including X-ray diffraction, scanning electron microscopy, microwave plasma atomic emission spectroscopy, thermogravimetric analysis, contact angle measurements, nitrogen sorption analysis, mercury intrusion porosimetry, filtration efficiency, and virucidal tests, was used to understand the interdependence of the materials’ physical characteristics and biological effects, as well as to determine their suitability for application as antiviral materials in air filtration systems. Results: All the filter materials tested demonstrated very high particle filtration efficiency (≥98.0%). The material embedded with copper nanoclusters showed strong virucidal efficacy against the SARS-CoV-2 alpha variant, achieving an approximately 1000-fold reduction in infectious virions within 12 h. The fibrous nanowire polymer functionalized with zinc nanoclusters was the most effective material against the human influenza A virus strain A/WSN/1933 (H1N1). Conclusions: The materials with Cu nanoclusters can be used with high efficiency to passivate and kill the SARS-CoV-2 alpha variant virions, and Zn nanoclusters modified activated porous membranes for killing human influenza A virus A7WSN/1933 (H1N1) virions. Full article

The COVID-19 pandemic has presented significant challenges to global healthcare, bringing out the urgent need for reliable diagnostic tools. Computed Tomography (CT) scans have proven instrumental in detecting COVID-19-induced lung abnormalities. This study introduces Convolutional Neural Network, Graph Neural Network, and Vision Transformer (ViTGNN), an advanced hybrid model designed to enhance SARS-CoV-2 detection by combining Graph Neural Networks (GNNs) for feature extraction with Vision Transformers (ViTs) for classification. Using the strength of CNN and GNN to capture complex relational structures and the ViT capacity to classify global contexts, ViTGNN achieves a comprehensive representation of CT scan data. The model was evaluated on a SARS-CoV-2 CT scan dataset, demonstrating superior performance across all metrics compared to baseline models. The model achieved an accuracy of 95.98%, precision of 96.07%, recall of 96.01%, F1-score of 95.98%, and AUC of 98.69%, outperforming existing approaches. These results indicate that ViTGNN is an effective diagnostic tool that can be applied beyond COVID-19 detection to other medical imaging tasks. Full article

Background/Objectives: For viral entry into host cells, the spike (S) protein of coronavirus (CoV) uses its S1 domain to bind to the host receptor and S2 domain to mediate the fusion between virion and cellular membranes. The S1 domain acquired multiple mutations as the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) evolved to give rise to Variant of Concerns (VOCs) but the S2 domain has limited changes. In particular, the stem helix in S2 did not change significantly and it is fairly well-conserved across multiple beta-CoVs. In this study, we generated a murine mAb 7B2 binding to the stem helix of SARS-CoV-2. Methods: MAb 7B2 was isolated from immunized mouse and its neutralization activity was evaluated using microneutralization, plaque reduction and cell–cell fusion assays. Bio-layer interferometry was used to measure binding affinity and AlphaFold3 was used to model the antibody–antigen interface. Results: MAb 7B2 has lower virus neutralizing and membrane block activities when compared to a previously reported stem helix-binding human mAb S2P6. Alanine scanning and AlphaFold3 modeling reveals that residues K1149 and D1153 in S form a network of polar interactions with the heavy chain of 7B2. Conversely, S2P6 binding to S is not affected by alanine substitution at K1149 and D1153 as indicated by the high ipTM scores in the predicted S2P6-stem helix structure. Conclusions: Our detailed characterization of the mechanism of inhibition of 7B2 reveals its distinctive binding model from S2P6 and yields insights on multiple neutralizing and highly conserved epitopes in the S2 domain which could be key components for pan-CoV vaccine development. Full article

To satisfy the requirement of the modern spaceborne synthetic aperture radar (SAR) system, SAR imaging mode design makes a trade-off between resolution and swath coverage by controlling radar antenna sweeping. Existing spaceborne SAR systems can perform earth observation missions well in various modes, but they still face challenges in data acquisition, storage, and transmission, especially for high-resolution wide-swath imaging. In the past few years, sparse signal processing technology has been introduced into SAR to try to solve these problems. In addition, sparse SAR imaging shows huge potential to improve system performance, such as offering wider swath coverage and higher recovered image quality. In this paper, the design scheme of spaceborne sparse SAR imaging modes is systematically introduced. In the mode design, we first design the beam positions of the sparse mode based on the corresponding traditional mode. Then, the essential parameters are calculated for system performance analysis based on radar equations. Finally, a sparse SAR imaging method based on mixed-norm regularization is introduced to obtain a high-quality image of the considered scene from the data collected by the designed sparse modes. Compared with the traditional mode, the designed sparse mode only requires us to obtain a wider swath coverage by reducing the pulse repetition rate (PRF), without changing the existing on-board system hardware. At the same time, the reduction in PRF can significantly reduce the system data rate. The problem of the azimuth ambiguity signal ratio (AASR) increasing from antenna beam scanning can be effectively solved by using the mixed-norm regularization-based sparse SAR imaging method. Full article

Arc scanning synthetic aperture radar (ArcSAR) can achieve high-resolution panoramic imaging and retrieve submillimeter-level deformation information. To monitor buildings in a city scenario, ArcSAR must be lightweight; have a high resolution, a mid-range (around a hundred meters), and low power consumption; and be cost-effective. In this study, a novel high-resolution wide-beam single-chip millimeter-wave (mmwave) ArcSAR system, together with an imaging algorithm, is presented. First, to handle the non-uniform azimuth sampling caused by motor motion, a high-accuracy angular coder is used in the system design. The coder can send the radar a hardware trigger signal when rotated to a specific angle so that uniform angular sampling can be achieved under the unstable rotation of the motor. Second, the ArcSAR’s maximum azimuth sampling angle that can avoid aliasing is deducted based on the Nyquist theorem. The mathematical relation supports the proposed ArcSAR system in acquiring data by setting the sampling angle interval. Third, the range cell migration (RCM) phenomenon is severe because mmwave radar has a wide azimuth beamwidth and a high frequency, and ArcSAR has a curved synthetic aperture. Therefore, the fourth-order RCM model based on the range-Doppler (RD) algorithm is interpreted with a uniform azimuth angle to suit the system and implemented. The proposed system uses the TI 6843 module as the radar sensor, and its azimuth beamwidth is 64°. The performance of the system and the corresponding imaging algorithm are thoroughly analyzed and validated via simulations and real data experiments. The output image covers a 360° and 180 m area at an azimuth resolution of 0.2°. The results show that the proposed system has good application prospects, and the design principles can support the improvement of current ArcSARs. Full article

Despite the climate crisis, a significant barrier to sustainability is limitations to the current accounting and reporting system. These deficiencies, mean the global financial system continues to invest trillions of dollars annually in environmentally sub-optimal projects. To catalyze the economic transition away from fossil-fuel and plastic configurations to more sustainable ones, sustainability accounting and reporting (SAR) is imperative. However, theoretical contention, pragmatic concerns, and costs stoke strong resistance to SAR. The research used ablative thematic analysis to apply hermeneutic phenomenology. First, it scanned the backdrop to the SAR problem and identified a corpus of recent literature from key associated institutions. The initial interpretation of the texts disentangled SAR’s conflicting threads and generated three themes of ‘climate crisis’ and ‘conservative’ or more ‘radical’ SAR reform paradigms. Iteratively harnessing these thematic lenses, the investigation re-examined the SAR literature corpus. The textual ‘dialogue’ generated understanding of the fragmented SAR responses to the climate crisis. Accordingly, the research reformulated its first theme to ‘dystopic climate crisis fragmentation’ and refined the other themes to take account of materiality and the split between Anglo-Saxon (IFRS, SSAB) or global (UN) and continental European accounting institutions (EU, GRI). Conservatives retain a single materiality investor-focus and concede only incremental standard improvements. Radicals seek to implement double materiality with a broader spectrum of stakeholders in mind. Both approaches have theoretical as well as pragmatic advantages and disadvantages, so the SAR contention rumbles on. Whilst the standard-setting landscape is evolving, disagreements remain. Its roots of contention are philosophical and pragmatic. Philosophically, radicals strive to temper libertarian anarcho-capitalist proclivities and broaden firm responsibility. Pragmatically, social, or environmental externalities are problematic to assign or measure. Given vested interests in the destructive status quo, it would be naïve to expect a harmonious SAR Ithaca to emerge anytime soon. Yet the challenges impel an intensification of SAR dialogue and concrete actions. Rather than a scientifically nomothetic contribution, the paper provides a qualitative, artful interpretation of a complex, contentious but crucial field. Full article

The acquisition of electroencephalography (EEG) concurrently with functional magnetic resonance imaging (fMRI) requires a careful consideration of the health hazards resulting from interactions between the scanner’s electromagnetic fields and EEG recording equipment. The primary safety concern is excessive RF-induced heating of the tissue in the vicinity of electrodes. We have previously demonstrated that concurrent intracranial EEG (icEEG) and fMRI data acquisitions (icEEG-fMRI) can be performed with acceptable risk in specific conditions using a head RF transmit coil. Here, we estimate the potential additional heating associated with the addition of scalp EEG electrodes using a body transmit RF coil. In this study, electrodes were placed in clinically realistic positions on a phantom in two configurations: (1) icEEG electrodes only, and (2) following the addition of subdermal scalp electrodes. Heating was measured during MRI scans using a body transmit coil with a high specific absorption rate (SAR), TSE (turbo spin echo), and low SAR gradient-echo EPI (echo-planar imaging) sequences. During the application of the high-SAR sequence, the maximum temperature change for the intracranial electrodes was +2.8 °C. The addition of the subdural scalp EEG electrodes resulted in a maximum temperature change for the intracranial electrodes of 2.1 °C and +0.6 °C across the scalp electrodes. For the low-SAR sequence, the maximum temperature increase across all intracranial and scalp electrodes was +0.7 °C; in this condition, the temperature increases around the intracranial electrodes were below the detection level. Therefore, in the experimental conditions (MRI scanner, electrode, and wire configurations) used at our centre for icEEG-fMRI, adding six scalp EEG electrodes did not result in significant additional localised RF-induced heating compared to the model using icEEG electrodes only. Full article

In this study, we conducted a comprehensive analysis of the interactions between the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein and four neutralizing antibodies—S309, S304, CYFN1006, and VIR-7229. Using integrative computational modeling that combined all-atom molecular dynamics (MD) simulations, mutational scanning, and MM-GBSA binding free energy calculations, we elucidated the structural, energetic, and dynamic determinants of antibody binding. Our findings reveal distinct dynamic binding mechanisms and evolutionary adaptation driving the broad neutralization effect of these antibodies. We show that S309 targets conserved residues near the ACE2 interface, leveraging synergistic van der Waals and electrostatic interactions, while S304 focuses on fewer but sensitive residues, making it more susceptible to escape mutations. The analysis of CYFN-1006.1 and CYFN-1006.2 antibody binding highlights broad epitope coverage with critical anchors at T345, K440, and T346, enhancing its efficacy against variants carrying the K356T mutation, which caused escape from S309 binding. Our analysis of broadly potent VIR-7229 antibody binding to XBB.1.5 and EG.5 Omicron variants emphasized a large and structurally complex epitope, demonstrating certain adaptability and compensatory effects to F456L and L455S mutations. Mutational profiling identified key residues crucial for antibody binding, including T345, P337, and R346 for S309 as well as T385 and K386 for S304, underscoring their roles as evolutionary “weak spots” that balance viral fitness and immune evasion. The results of the energetic analysis demonstrate a good agreement between the predicted binding hotspots, reveal distinct energetic mechanisms of binding, and highlight the importance of targeting conserved residues and diverse epitopes to counteract viral resistance. Full article