Initial Step Research Articles

Disulfide bridge-dependent dimerization triggers FGF2 membrane translocation into the extracellular space

Fibroblast growth factor 2 (FGF2) exits cells by direct translocation across the plasma membrane, a type I pathway of unconventional protein secretion. This process is initiated by phosphatidylinositol-4,5-bisphosphate (PI(4,5)P2)-dependent formation of highly dynamic FGF2 oligomers at the inner plasma membrane leaflet, inducing the formation of lipidic membrane pores. Cell surface heparan sulfate chains linked to glypican-1 (GPC1) capture FGF2 at the outer plasma membrane leaflet, completing FGF2 membrane translocation into the extracellular space. While the basic steps of this pathway are well understood, the molecular mechanism by which FGF2 oligomerizes on membrane surfaces remains unclear. In the current study, we demonstrate the initial step of this process to depend on C95-C95 disulfide-bridge-mediated FGF2 dimerization on membrane surfaces, producing the building blocks for higher FGF2 oligomers that drive the formation of membrane pores. We find FGF2 with a C95A substitution to be defective in oligomerization, pore formation, and membrane translocation. Consistently, we demonstrate a C95A variant of FGF2 to be characterized by a severe secretion phenotype. By contrast, while also important for efficient FGF2 secretion from cells, a second cysteine residue on the molecular surface of FGF2 (C77) is not involved in FGF2 oligomerization. Rather, we find C77 to be part of the interaction interface through which FGF2 binds to the α1 subunit of the Na,K-ATPase, the landing platform for FGF2 at the inner plasma membrane leaflet. Using cross-linking mass spectrometry, atomistic molecular dynamics simulations combined with a machine learning analysis and cryo-electron tomography, we propose a mechanism by which disulfide-bridged FGF2 dimers bind with high avidity to PI(4,5)P2 on membrane surfaces. We further propose a tight coupling between FGF2 secretion and the formation of ternary signaling complexes on cell surfaces, hypothesizing that C95-C95-bridged FGF2 dimers are functioning as the molecular units triggering autocrine and paracrine FGF2 signaling.

Climate Resilience through AI-Driven Hurricane Damage Assessments

Evolving hurricane patterns intensified by climate change are expected to exacerbate economic hardships on coastal communities. Climate resilience for these communities requires both the capability to recover rapidly from devastating storms, and the ability to develop an accurate and actionable understanding of vulnerabilities to reduce the impact of future storms. Available data from past storms can provide invaluable insight in addressing both these requirements. Post-disaster preliminary damage assessments (PDAs) are a crucial initial step toward a rapid recovery. They also provide the most accurate information on the performance of various types of dwellings after the storm. Traditional door-to-door inspection methods are time-consuming and can hinder efficient resource allocation by governments in the aftermath. To address this, researchers have proposed automated PDA frameworks, often utilizing data from satellites, combined with deep convolutional neural networks. However, before such frameworks can be adopted in practice, the accuracy and fidelity of predictions of damage level at the scale of an entire building must be comparable to human assessments. To bridge this gap, we present an innovative PDA framework that leverages Ultra-High-Resolution Aerial (UHRA) images alongside state-of-the-art transformer models for multi-class damage predictions across entire buildings. Our approach leverages vast amounts of unlabeled data to enhance accuracy of prediction and generalization capabilities. Through a series of experiments, we evaluate the influence of incorporating unlabeled data, and transformer models. By integrating UHRA images and semi-supervised transformer models, our findings indicate that this framework overcomes critical limitations associated with satellite imagery and traditional CNN models, achieving an 88% multiclass accuracy, ultimately leading to more precise, efficient, and reliable damage assessments that are a first step towards building more climate resilient societies.

Bioavailability transition path of phosphorus species during the sewage sludge incineration process

Sewage sludge incineration ash (SSIA) is rich in phosphorus (P), thus being considered as a reliable source of phosphorus recovery. Different P species behaved significant bioavailability. Based on this, a comprehensive investigation into the bioavailability transition path of P species during sewage sludge (SS) incineration was conducted. P predominantly existed in the form of inorganic phosphorus (IP) in SS with a higher concentration of non-apatite inorganic phosphorus (NAIP) and less concentration of apatite inorganic phosphorus (AP). During the SS incineration process, OP existed in the flocs and cell structures of SS underwent destruction, the released P then combined with metal elements such as Ca, Mg, Fe, and Al to form AP species (Ca/Mg–P) and NAIP species (Fe/Al/Mn–P), and the NAIP decomposition to release into gas phase. This was the initial step for enhancing the bioavailability of P species. As temperature increased and the incineration process progressed, the low-temperature-resistant NAIP dissociated, and the metal-binding sites of Al, Fe and Mn in NAIP species were gradually replaced by the Ca and Mg thus forming thermal stability AP species (Ca/Mg–P, such as CaHPO4, Ca2PO4Cl, and Mg3(PO4)2 et al.). This step was crucial for the bioavailability improvement of P species during the incineration process. Therefore, the IP proportions in TP were extremely high (＞98%), and this value gradually increased as incineration temperature raised. The higher incineration temperature, the lower NAIP concentration and higher AP concentration. Besides, additives such as coal/rice husk/eggshell played a significant affect. Additives wither higher Ca content were inclined to react with P to form Ca/Mg–P (AP), while the presence of SO2 would react with Ca metals to form CaSO4 thus inhibiting the formation of AP species (such as CaHPO4 and CaPO4Cl). This results could provide theoretical support for the efficient and directional migration of P during sewage sludge incineration.

Penerapan Model Decision Tree Menggunakan Python Untuk Prediksi Faktor Dominan Penyebab Penyakit Stroke

Stroke is known as a disease caused by rupture of blood vessels in the brain or blockage of blood vessels in the brain. Disruption of the blood supply to the brain can result in damage to brain cells which results in damage to brain function. According to the World Health Organization (WHO) stroke is one of the highest causes of death worldwide, because almost 85% of the causes of death in the world are due to stroke. Current developments in science and technology require research to analyze stroke patient data so that the dominant factors that lead to stroke can be identified. This is an initial step that can be taken to address these problems to reduce the risk of death caused by stroke. In this study, the analysis was carried out by implementing a decision tree algorithm using python because the decision tree has good accuracy 91% in making predictions. With the decision tree formed from this algorithm, it will be easy to see the symptoms, starting from those who are most at risk to those who have the lowest risk of causing stroke

Association of methylation silencing of ULK2 via epithelial-mesenchymal transition and differentiated gastric cancers.

404 Background: Diffuse-type gastric cancers (DGC) typically have a poor prognosis related to their invasion and metastasis, in which the epithelial–mesenchymal transition (EMT) is the initiation step. ULK2 plays a role in the autophagy initiation, which might provide a survival advantage in cancer cells. Although knock-down of ULK2 reportedly induces autophagy and EMT in a lung cancer cell line, the mechanism of EMT via the downregulation of ULK2, as well as its clinical significance, remains yet unclear. The present study, therefore, aims at clarifying this mechanism and its clinical significance in gastric cancers. Methods: We examined ULK2 mRNA expression in gastric cancer tissues and normal gastric tissues of healthy people. The effects of knock-downed ULK2 were examined in two gastric cancer cells, which were investigated in terms of their gene expression changes by the mRNA microarray. Furthermore, to investigate the carcinogenic process from normal gastric epithelial cells, we used RGE cells, which were conditionally immortalized normal gastric epithelial cells developed from a transgenic rat. Results: ULK2 mRNA expression of gastric cancer tissues was significantly lower than H. pylori-negative normal tissues. ULK2 was strongly expressed in normal tissues and intestinal-type gastric cancers (IGC) but was scarcely expressed in DGC by immunohistochemical staining. Furthermore, we found that the ULK2 methylation level of gastric cancer tissues was higher than H. pylori-negative normal tissues and IGC. Then, we validated whether knock-down of ULK2 could induce autophagy, cell migration, and EMT in NUGC3 and MKN45 cells. Using mRNA microarray analysis, we confirmed that knock-down of ULK2 changed expressions of oncogenic genes associated with cell migration and EMT. Autophagy inhibitor suppressed cell migration and EMT induced by knock-down of ULK2 in NUGC3 and MKN45. Additionally, we found that knock-down of Ulk2 induced apoptosis in normal gastric epithelial cells. Conclusions: Methylation silencing of ULK2 in gastric cancer cells could induce cell migration and EMT by means of autophagy induction, causing transformation to poorly differentiated cancers.

Deep Learning for Holistic Mental Illness Diagnosis with Multimodal Imaging

Detecting and diagnosing mental illnesses is a complex task due to the heterogeneous nature of these conditions, which encompass various types and subtypes. Timely identification and diagnosis are essential for advancing mental health research, improving early intervention, and developing effective therapies. However, existing methods have primarily focused on categorizing and diagnosing single mental illness types, often prioritizing patient survival over comprehensive treatment. This research introduces a deep learning-based approach to establish a universal framework for the detection, diagnosis, symptom-based prediction, and screening of diverse mental illnesses, their subtypes, and associated factors using a diverse dataset comprising images and clinical scans. The proposed architecture leverages a VGG-19-based 3D-convolutional neural network for robust feature extraction and employs a random forest algorithm for regression tasks. To create a comprehensive dataset, we incorporate results from the DAIC-WOZ laboratory dataset, imaging studies, and biopsy reports, moving beyond sole reliance on clinical images. The initial step involves distinguishing between healthy and unhealthy depression, sleep disorder, Alzheimer's, schizophrenia, and epilepsy conditions and subsequently classifying depression, sleep disorder, Alzheimer's, schizophrenia, and epilepsy cases into their specific subtypes while assessing their severity and growth patterns. Our model is designed to predict risk levels at various time intervals, utilizing the available pertinent factors consistently across different diagnostic tools. Our results demonstrate promising accuracy, with a 98.80% success rate in classifying them into their respective subtypes, a sensitivity of 98.24%, and a specificity of 98.49%. This research represents a significant step toward a more holistic and precise approach to mental illness detection, diagnosis, and management, performing 4.74% better than other state-of-the-art AI models and offering potential benefits for individuals and mental health professionals alike.

To Be or Not To Be… Cooperative? Trimetallic Catalysts for the Ring‐Opening Polymerisation of Cyclic Esters

AbstractMultimetallic catalysts have emerged as a promising route to enhance catalyst performance in cyclic ester ring‐opening polymerisation (ROP), as these complexes can outperform the monometallic analogues in terms of reactivity and/or polymerisation control. Such enhancements are often attributed to “multimetallic cooperativity”, yet the origins of this cooperativity often remain unclear. Here, we report the synthesis and characterisation of two trimetallic Al‐salen complexes (L1(AlMe)3 and L1(AlEt)3), containing three Al‐salen subunits in close proximity, and their monometallic analogues (L2(AlMe) and L2(AlEt)). These complexes have been applied as catalysts for cyclic ester ROP under a range of conditions, to probe their potential for cooperative behaviour. Trimetallic L1(AlMe)3 and L1(AlEt)3 both display high activities in rac‐lactide ROP, giving kobs values of up to 11×10−3 min−1. Yet careful benchmarking against the monometallic complexes reveals that whether these systems display multimetallic cooperativity or not depends upon the reaction conditions. Detailed kinetic and spectroscopic studies into the origins of cooperativity revealed that the neighbouring metals play a key role in the initiation step, rather than propagation. Overall, these studies highlight the importance of understanding the reaction conditions in order to accurately define whether a catalyst displays multimetallic cooperativity.

Streamlined enzymatic synthesis of human milk fat substitutes

The positional distribution of palmitic acid (PA) in human milk fat substitutes (HMFSs) plays a pivotal role in mimicking the nutritional profile of human milk fat for nourishing non-breastfed infants. This study innovatively introduced a streamlined enzymatic process for preparing HMFSs rich in sn-2 PA using palm stearin, a PA-rich source without the necessity for positional distribution of PA. The initial step involved enhancing the sn-2 PA concentration through enzymatic interesterification using Lipase UM1, which exhibited superior catalytic efficiency than Novozym 435. This process increased the sn-2 PA level from 40.98 % to 64.51 %. Subsequently, acidolysis was employed to reduce PA levels by replacing PA at sn-1,3 positions using sn-1,3-regioselective lipases. The PA content decreased from 60.64 % to 26.73 %, simultaneously raising the relative sn-2 PA concentration to 71.57 %, meeting the benchmarks for HMFSs. This study establishes a robust conceptual framework for the prospective industrial synthesis of HMFSs.

Differences in regulation mechanisms of glutamine synthetases from methanogenic archaea unveiled by structural investigations

Glutamine synthetases (GS) catalyze the ATP-dependent ammonium assimilation, the initial step of nitrogen acquisition that must be under tight control to fit cellular needs. While their catalytic mechanisms and regulations are well-characterized in bacteria and eukaryotes, only limited knowledge exists in archaea. Here, we solved two archaeal GS structures and unveiled unexpected differences in their regulatory mechanisms. GS from Methanothermococcus thermolithotrophicus is inactive in its resting state and switched on by 2-oxoglutarate, a sensor of cellular nitrogen deficiency. The enzyme activation overlays remarkably well with the reported cellular concentration for 2-oxoglutarate. Its binding to an allosteric pocket reconfigures the active site through long-range conformational changes. The homolog from Methermicoccus shengliensis does not harbor the 2-oxoglutarate binding motif and, consequently, is 2-oxoglutarate insensitive. Instead, it is directly feedback-inhibited through glutamine recognition by the catalytic Asp50ʹ-loop, a mechanism common to bacterial homologs, but absent in M. thermolithotrophicus due to residue substitution. Analyses of residue conservation in archaeal GS suggest that both regulations are widespread and not mutually exclusive. While the effectors and their binding sites are surprisingly different, the molecular mechanisms underlying their mode of action on GS activity operate on the same molecular determinants in the active site.

Reaping the benefits of liquid handlers for high-throughput gene expression profiling in a marine model invertebrate

BackgroundModern high-throughput technologies enable the processing of a large number of samples simultaneously, while also providing rapid and accurate procedures. In recent years, automated liquid handling workstations have emerged as an established technology for reproducible sample preparation. They offer flexibility, making them suitable for an expanding range of applications. Commonly, such approaches are well-developed for experimental procedures primarily designed for cell-line processing and xenobiotics testing. Conversely, little attention is focused on the application of automated liquid handlers in the analysis of whole organisms, which often involves time-consuming laboratory procedures.ResultsHere, we present a fully automated workflow for all steps, from RNA extraction to real-time PCR processing, for gene expression quantification in the ascidian marine model Ciona robusta. For procedure validation, we compared the results obtained with the liquid handler with those of the classical manual procedure. The outcome revealed comparable results, demonstrating a remarkable time saving particularly in the initial steps of sample processing.ConclusionsThis work expands the possible application fields of this technology to whole-body organisms, mitigating issues that can arise from manual procedures. By minimizing errors, avoiding cross-contamination, decreasing hands-on time and streamlining the procedure, it could be employed for large-scale screening investigations.

«Отложенное правосудие» в рамках третейского разбирательства

The article explores the issue of giving substance to the concept of “justice” within the law protection system in the Russian Federation. The author considers the so-called “broad” and “narrow” approach to understanding the category of “justice” and favors a narrow understanding. The article proposes a novel concept of viewing enforcement in the context of arbitration protection as the initial step in the state court’s fulfillment of its justice function culminating in the state’s judicial oversight of the arbitral award.

Regulation of tissue factor activity by interaction with the first PDZ domain of MAGI1

BackgroundTissue factor (TF) activity is stringently regulated through processes termed encryption. Post-translational modification of TF and its interactions with various protein and lipid moieties allows for a multi-step de-encryption of TF and procoagulant activation. Membrane-associated guanylate kinase-with inverted configuration (MAGI) proteins are known to regulate the localisation and activity of a number of proteins including cell-surface receptors.MethodsThe interaction of TF with MAGI1 protein was examined as a means of regulating TF activity. MDA-MB-231 cell line was used which express TF and MAGI1, and respond well to protease activated receptor (PAR)2 activation. Proximity ligation assay (PLA), co-immunoprecipitation and pull-down experiments were used to examine the interaction of TF with MAGI1-3 proteins and to investigate the influence of PAR2 activation. Furthermore, by cloning and expressing the PDZ domains from MAGI1, the TF-binding domain was identified. The ability of the recombinant PDZ domains to act as competitors for MAGI1, allowing the induction of TF procoagulant and signalling activity was then examined.ResultsPLA and fluorescence microscopic analysis indicated that TF predominantly associates with MAGI1 and less with MAGI2 and MAGI3 proteins. The interaction of TF with MAGI1 was also demonstrated by both co-immunoprecipitation of TF with MAGI1, and co-immunoprecipitation of MAGI1 with TF. Moreover, activation of PAR2 resulted in reduction in the association of these two proteins. Pull-down assays using TF-cytoplasmic domain peptides indicated that the phosphorylation of Ser253 within TF prevents its association with MAGI1. Additionally, the five HA-tagged PDZ domains of MAGI1 were overexpressed separately, and the putative TF-binding domain was identified as PDZ1 domain. Expression of this PDZ domain in cells significantly augmented the TF activity measured both as thrombin-generation and also TF-mediated proliferative signalling.ConclusionsOur data indicate a stabilising interaction between TF and the PDZ-1 domain of MAGI1 and demonstrate that the activation of PAR2 disrupts this interaction. The release of TF from MAGI1 appears to be an initial step in TF de-encryption, associated with increased TF-mediated procoagulant and signalling activities. This mechanism is also likely to lead to further interactions and modifications leading to further enhancement of procoagulant activity, or the release of TF.

Electron-beam-promoted fullerene dimerization in nanotubes: insights from DFT computations.

Fullerene dimerization inside a peapod is analyzed at DFT level by characterizing the stationary points and deriving the energy profile of the initial and reversible process named phase 1. We find that the barriers for the radical cation mechanism are significantly lower than those found for the neutral pathway. The peapod is mainly providing one-dimensional confinement for the reaction to take place in a more efficient way. Car-Parrinello metadynamics simulations provide hints on structures for the initial steps of the irreversible phase 2 where bond formation and breaking lead to important structural reorganizations within the coalescence process.

On the Determination of Lagrange Multipliers for a Weighted LASSO Problem Using Geometric and Convex Analysis Techniques

Compressed Sensing (CS) encompasses a broad array of theoretical and applied techniques for recovering signals, given partial knowledge of their coefficients, cf. Candés (C. R. Acad. Sci. Paris, Ser. I 346, 589–592 (2008)), Candés et al. (IEEE Trans. Inf. Theo (2006)), Donoho (IEEE Trans. Inf. Theo. 52(4), (2006)), Donoho et al. (IEEE Trans. Inf. Theo. 52(1), (2006)). Its applications span various fields, including mathematics, physics, engineering, and several medical sciences, cf. Adcock and Hansen (Compressive Imaging: Structure, Sampling, Learning, p. 2021), Berk et al. (2019 13th International conference on Sampling Theory and Applications (SampTA) pp. 1-5. IEEE (2019)), Brady et al. (Opt. Express 17(15), 13040–13049 (2009)), Chan (Terahertz imaging with compressive sensing. Rice University, USA (2010)), Correa et al. (2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) pp. 7789–7793 (2014, May) IEEE), Gao et al. (Nature 516(7529), 74–77 (2014)), Liu and Kang (Opt. Express 18(21), 22010–22019 (2010)), McEwen and Wiaux (Mon. Notices Royal Astron. Soc. 413(2), 1318–1332 (2011)), Marim et al. (Opt. Lett. 35(6), 871–873 (2010)), Yu and Wang (Phys. Med. Biol. 54(9), 2791 (2009)), Yu and Wang (Phys. Med. Biol. 54(9), 2791 (2009)). Motivated by our interest in the mathematics behind Magnetic Resonance Imaging (MRI) and CS, we employ convex analysis techniques to analytically determine equivalents of Lagrange multipliers for optimization problems with inequality constraints, specifically a weighted LASSO with voxel-wise weighting. We investigate this problem under assumptions on the fidelity term Ax-b22\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\left\\Vert Ax-b\\right\\Vert _2^2$$\\end{document}, either concerning the sign of its gradient or orthogonality-like conditions of its matrix. To be more precise, we either require the sign of each coordinate of 2(Ax-b)TA\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$2(Ax-b)^TA$$\\end{document} to be fixed within a rectangular neighborhood of the origin, with the side lengths of the rectangle dependent on the constraints, or we assume ATA\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$A^TA$$\\end{document} to be diagonal. The objective of this work is to explore the relationship between Lagrange multipliers and the constraints of a weighted variant of LASSO, specifically in the mentioned cases where this relationship can be computed explicitly. As they scale the regularization terms of the weighted LASSO, Lagrange multipliers serve as tuning parameters for the weighted LASSO, prompting the question of their potential effective use as tuning parameters in applications like MR image reconstruction and denoising. This work represents an initial step in this direction.

Alterations in the chromatin packaging, driven by transcriptional activity, revealed by AFM

BackgroundThe gene expression differs in the nuclei of normal and malignant mammalian cells, and transcription is a critical initial step, which defines the difference. The mechanical properties of transcriptionally active chromatin are still poorly understood. Recently we have probed transcriptionally active chromatin of the nuclei subjected to mechanical stress, by Atomic Force Microscopy (AFM) [1]. Nonetheless, a systematic study of the phenomenon is needed. MethodsNuclei were deformed and studied by AFM. Non-deformed nuclei were studied by fluorescence confocal microscopy. Their transcriptional activity was studied by RNA electrophoresis. ResultsThe malignant nuclei under the study were stable to deformation and assembled of 100–300 nm beads-like units, while normal cell nuclei were prone to deformation. The difference in stability to deformation of the nuclei correlated with DNA supercoiling, and transcription-depended units were responsive to supercoils breakage. The inhibitors of the topoisomerases I and II disrupted supercoiling and made the malignant nucleus prone to deformation. Cell nuclei treatment with histone deacetylase inhibitors (HDACIs) preserved the mechanical stability of deformed malignant nuclei and, at the same time, made it possible to observe chromatin decondensation up to 20–60 nm units. The AFM results were supplemented with confocal microscopy and RNA electrophoresis data. ConclusionsSelf-assembly of transcriptionally active chromatin and its decondensation, driven by DNA supercoiling-dependent rigidity, was visualized by AFM in the mechanically deformed nuclei. General significanceWe demonstrated that supercoiled DNA defines the transcription mechanics, and hypothesized the nuclear mechanics in vivo should depend on the chromatin architecture.

Deciphering the Mechanism of On-Surface Dehydrogenative C-C Coupling Reactions.

On-surface synthesis has proven to be a powerful approach for fabricating various low-dimensional covalent nanostructures with atomic precision that could be challenging for conventional solution chemistry. Dehydrogenative Caryl-Caryl coupling is one of the most popular on-surface reactions, of which the mechanisms, however, have not been well understood due to the lack of microscopic insights into the intermediates that are fleetingly existing under harsh reaction conditions. Here, we bypass the most energy-demanding initiation step to generate and capture some of the intermediates at room temperature (RT) via the cyclodehydrobromination of 1-bromo-8-phenylnaphthalene on a Cu(111) surface. Bond-level scanning probe imaging and manipulation in combination with DFT calculations allow for the identification of chemisorbed radicals, cyclized intermediates, and dehydrogenated products. These intermediates correspond to three main reaction steps, namely, debromination, cyclization (radical addition), and H elimination. H elimination is the rate-determining step as evidenced by the predominant cyclized intermediates. Furthermore, we reveal a long-overlooked pathway of dehydrogenation, namely, atomic hydrogen-catalyzed H shift and elimination, based on the observation of intermediates for H shift and superhydrogenation and the proof of a self-amplifying effect of the reaction. This pathway is further corroborated by comprehensive theoretical analysis on the reaction thermodynamics and kinetics.

The universal suppressor mutation restores membrane budding defects in the HSV-1 nuclear egress complex by stabilizing the oligomeric lattice.

Nuclear egress is an essential process in herpesvirus replication whereby nascent capsids translocate from the nucleus to the cytoplasm. This initial step of nuclear egress-budding at the inner nuclear membrane-is coordinated by the nuclear egress complex (NEC). Composed of the viral proteins UL31 and UL34, NEC deforms the membrane around the capsid as the latter buds into the perinuclear space. NEC oligomerization into a hexagonal membrane-bound lattice is essential for budding because NEC mutants designed to perturb lattice interfaces reduce its budding ability. Previously, we identified an NEC suppressor mutation capable of restoring budding to a mutant with a weakened hexagonal lattice. Using an established in-vitro budding assay and HSV-1 infected cell experiments, we show that the suppressor mutation can restore budding to a broad range of budding-deficient NEC mutants thereby acting as a universal suppressor. Cryogenic electron tomography of the suppressor NEC mutant lattice revealed a hexagonal lattice reminiscent of wild-type NEC lattice instead of an alternative lattice. Further investigation using x-ray crystallography showed that the suppressor mutation promoted the formation of new contacts between the NEC hexamers that, ostensibly, stabilized the hexagonal lattice. This stabilization strategy is powerful enough to override the otherwise deleterious effects of mutations that destabilize the NEC lattice by different mechanisms, resulting in a functional NEC hexagonal lattice and restoration of membrane budding.

TunGPR: Enhancing data-driven maintenance for tunnel linings through synthetic datasets, deep learning and BIM

Non-destructive Testing (NDT) techniques and data-driven technologies are increasingly applied in underground infrastructure maintenance, which can facilitate predictive monitoring for informed decision-making. Ground Penetrating Radar (GPR) is extensively utilised in rapid condition assessment of tunnel linings, particularly for detecting defects that lead to unforeseen changes of dielectric properties of materials. In this paper, a prototyped framework is proposed, namely TunGPR, for GPR-based tunnel lining assessment by incorporating Building Information Modelling (BIM), synthetic database and deep learning-enabled interpretation. The first module integrates laser-scanned point clouds and GPR Scan-to-BIM of tunnel lining with geological model. Subsequently, interoperability is achieved between the geo-integrated BIM and GPR simulation software. From the dielectric model retrieved from the BIM model, a database is established, considering a variety of condition combinations (i.e., voids, cavities, delamination, and water intrusion) leveraging domain randomisation and Finite-Difference Time-Domain (FDTD) modelling, as well as monitored field data. The dataset is then fed into the diagnostic module underpinned by a dual-rotational Convolutional Neural Network (CNN) that is customised to enhance accuracy and automation of hyperbola detection. Lastly, a preliminary risk assessment matrix is implemented into the BIM model for data management and action prioritisation. These efforts serve as an initial step to validate the feasibility and effectiveness of the GPR-enabled data-driven maintenance for tunnel linings in a BIM-centred framework.

Identification and characterization of GLYCEROLIPASE A1 for wound-triggered JA biosynthesis in Nicotiana benthamiana leaves.

Although many important discoveries have been made regarding the jasmonate signaling pathway, how jasmonate biosynthesis is initiated is still a major unanswered question in the field. Previous evidences suggest that jasmonate biosynthesis is limited by the availability of fatty acid precursor, such as ⍺-linolenic acid (⍺-LA). This indicates that the lipase responsible for releasing α-LA in the chloroplast, where early steps of jasmonate biosynthesis take place, is the key initial step in the jasmonate biosynthetic pathway. Nicotiana benthamiana glycerol lipase A1 (NbGLA1) is homologous to N. attenuata GLA1 (NaGLA1) which has been reported to be a major lipase in leaves for jasmonate biosynthesis. NbGLA1 was studied for its potential usefulness in a species that is more common in laboratories. Virus-induced gene silencing of both NbGLA1 and NbGLA2, another homolog, resulted in more than 80% reduction in jasmonic acid (JA) biosynthesis in wounded leaves. Overexpression of NbGLA1 utilizing an inducible vector system failed to increase JA, indicating that transcriptional induction of NbGLA1 is insufficient to trigger JA biosynthesis. However, co-treatment with wounding in addition to NbGLA1 induction increased JA accumulation several fold higher than the gene expression or wounding alone, indicating an enhancement of the enzyme activity by wounding. Domain-deletion of a 126-bp C-terminal region hypothesized to have regulatory roles increased NbGLA1-induced JA level. Together, the data show NbGLA1 to be a major lipase for wound-induced JA biosynthesis in N. benthamiana leaves and demonstrate the use of inducible promoter-driven construct of NbGLA1 in conjunction with its transient expression in N. benthamiana as a useful system to study its protein function.

Simulation of four-point bending tests for the viscoelastic fracture properties of concrete

Understanding the fracture properties of concrete, such as crack propagation behavior and fracture energy, is crucial for designing and evaluating concrete structures. Experimental results are insufficient and cannot be directly employed for a comprehensive analysis of the fracture behavior of concrete structures under load, particularly when considering concrete as viscoelastic with the presence of cracks. Recognizing the time and cost constraints of traditional experimental testing, this research leverages numerical simulations as a cost-effective alternative to determine viscoelastic material parameters. Thus, the critical evaluation of concrete fracture properties, fundamental for the design and assessment of concrete structures, is addressed. Employing a finite element method for four-point bending tests, the study systematically investigates parameters such as initial crack depth, displacement acceleration, and time step. The material properties of concrete are described using viscoelastic models. The findings provide valuable insights into crack propagation behavior and deformation characteristics, emphasizing the significant influence of the modulus of elasticity on both maximum load values and displacement. These findings contribute to a deeper understanding of the structure's response and underscore the importance of considering these parameters in similar simulations. The study highlights the importance of considering these parameters in simulations to enhance the understanding of concrete fracture behavior. The paper's contributions can extend to optimizing concrete mixtures, formulating repair strategies, and improving structural assessments. Further research is suggested to improve the accuracy of simulations and investigate material properties under various conditions.