Search Results (2,268)

Phosphorylation, a reversible and widespread post-translational modification of proteins, is essential for numerous cellular processes. However, due to technical limitations, large-scale detection of phosphorylation sites, especially those infected by SARS-CoV-2, remains a challenging task. To address this gap, we propose a method called GBMPhos, a novel method that combines convolutional neural networks (CNNs) for extracting local features, gating mechanisms to selectively focus on relevant information, and a bi-directional gated recurrent unit (Bi-GRU) to capture long-range dependencies within protein sequences. GBMPhos leverages a comprehensive set of features, including sequence encoding, physicochemical properties, and structural information, to provide an in-depth analysis of phosphorylation sites. We conducted an extensive comparison of GBMPhos with traditional machine learning algorithms and state-of-the-art methods. Experimental results demonstrate the superiority of GBMPhos over existing methods. The visualization analysis further highlights its effectiveness and efficiency. Additionally, we have established a free web server platform to help researchers explore phosphorylation in SARS-CoV-2 infections. The source code of GBMPhos is publicly available on GitHub. Full article

In an era of massive construction, damaged and aging infrastructure are becoming more common. Defects, such as cracking, spalling, etc., are main types of structural damage that widely occur. Hence, ensuring the safe operation of existing infrastructure through health monitoring has emerged as an important challenge facing engineers. In recent years, intelligent approaches, such as data-driven machines and deep learning crack detection have gradually dominated over traditional methods. Among them, the semantic segmentation using deep learning models is a process of the characterization of accurate locations and portraits of cracks using pixel-level classification. Most available studies rely on single-model knowledge to perform this task. However, it is well-known that the single model might suffer from low variance and low ability to generalize in case of data alteration. By leveraging the ensemble deep learning philosophy, a novel collaborative semantic segmentation of concrete cracks method called Co-CrackSegment is proposed. Firstly, five models, namely the U-net, SegNet, DeepCrack19, DeepLabV3-ResNet50, and DeepLabV3-ResNet101 are trained to serve as core models for the ensemble model Co-CrackSegment. To build the ensemble model Co-CrackSegment, a new iterative approach based on the best evaluation metrics, namely the Dice score, IoU, pixel accuracy, precision, and recall metrics is developed. Results show that the Co-CrackSegment exhibits a prominent performance compared with core models and weighted average ensemble by means of the considered best statistical metrics. Full article

A novel prototype based on the combination of a multi-junction, high-efficiency photovoltaic (PV) module and a supercapacitor (SC) able to self-power a wireless sensor node (WSN) for outdoor air quality monitoring has been developed and tested. A PV module with about an 8 cm² active area made of eight GaAs-based triple-junction solar cells with a nominal 29% efficiency was assembled and characterized under terrestrial clear-sky conditions. Energy is stored in a 4000 F/4.2 V supercapacitor with high energy capacity and a virtually infinite lifetime (10⁴ cycles). The node power consumption was tailored to the typical power consumption of miniaturized, low-consumption NDIR CO₂ sensors relying on an LED as the IR source. The charge/discharge cycles of the supercapacitor connected to the triple-junction PV module were measured under illumination with a Sun Simulator device at selected radiation intensities and different node duty cycles. Tests of the miniaturized prototype in different illumination conditions outdoors were carried out. A model was developed from the test outcomes to predict the maximum number of sensor samplings and data transmissions tolerated by the node, thus optimizing the WSN operating conditions to ensure its self-powering for years of outdoor deployment. The results show the self-powering ability of the WSN node over different insolation periods throughout the year, demonstrating its operation for a virtually unlimited lifetime without the need for battery substitution. Full article

Gold standard detection of SARS-CoV-2 by reverse transcription quantitative PCR (RT-qPCR) can achieve ultrasensitive viral detection down to a few RNA copies per sample. Yet, the lengthy detection and labor-intensive protocol limit its effectiveness in community screening. In view of this, a structural switching electrochemical aptamer-based biosensor (E-AB) targeting the SARS-CoV-2 nucleocapsid (N) protein was developed. Four N protein-targeting aptamers were characterized on an electrochemical cell configuration using square wave voltammetry (SWV). The sensor was investigated in an artificial saliva matrix optimizing the aptamer anchoring orientation, SWV interrogation frequency, and target incubation time. Rapid detection of the N protein was achieved within 5 min at a low nanomolar limit of detection (LOD) with high specificity. Specific N protein detection was also achieved in simulated positive saliva samples, demonstrating its feasibility for saliva-based rapid diagnosis. Further research will incorporate novel signal amplification strategies to improve sensitivity for early diagnosis. Full article

Lectins are a class of carbohydrate-binding proteins that may have antiviral activity by binding to the glycans on the virion surface to interfere with viral entry. We have identified a novel lectin (named Shictin) from Shiitake mushroom (Lentinula edodes)-derived vesicle-like nanoparticles (VLNs, or exosomes) that exhibits strong activity against the SARS-CoV-2 Omicron variant with an IC₅₀ value of 87 nM. Shictin contains 298 amino acids and consists of two unique domains (N-terminal and C-terminal domain). The N-terminal domain is the carbohydrate-binding domain (CBD) that is homologous with CBDs of other lectins, suggesting that Shictin inhibits SARS-CoV-2 infection by binding to the glycans on the virion surface to prevent viral entry. This finding demonstrates that exosomes of vegetables are a valuable source for the identification of antiviral lectins. Therefore, it is believed that lectins from vegetable VLNs have potential as antiviral therapeutic agents. Full article

Some respiratory viruses, such as Human Rhinovirus, SARS-CoV-2, and Enterovirus D-68 (EV-D68), share the feature of hijacking host lipids in order to generate specialised replication organelles (ROs) with unique lipid compositions to enable viral replication. We have recently uncovered a novel non-canonical function of the stimulator of interferon genes (STING) pathway, as a critical factor in the formation of ROs in response to HRV infection. The STING pathway is the main DNA virus sensing system of the innate immune system controlling the type I IFN machinery. Although it is well-characterised as part of the DNA sensor machinery, the STING function in RNA viral infections is largely unexplored. In the current study, we investigated whether other RO-forming RNA viruses, such as EV-D68 and SARS-CoV-2, can also utilise STING for their replication. Using genetic and pharmacological inhibition, we demonstrate that STING is hijacked by these viruses and is utilised as part of the viral replication machinery. STING also co-localises with glycolytic enzymes needed to fuel the energy for replication. The inhibition of STING leads to the modulation of glucose metabolism in EV-D68-infected cells, suggesting that it might also manipulate immunometabolism. Therefore, for RO-generating RNA viruses, STING seems to have non-canonical functions in membrane lipid re-modelling, and the formation of replication vesicles, as well as immunometabolism. Full article

In a time of climate change, population growth, and globalization, the risk of viral spread has significantly increased. The 21st century has already witnessed outbreaks of Severe Acute Respiratory Syndrome virus (SARS-CoV), Severe Acute Respiratory Syndrome virus 2 (SARS-CoV-2), Ebola virus and Influenza virus, among others. Viruses rapidly adapt and evade human immune systems, complicating the development of effective antiviral countermeasures. Consequently, the need for novel antivirals resilient to viral mutations is urgent. In this study, we developed a CRISPR-Cas13b system to target SARS-CoV-2. Interestingly, this system was also efficient against SARS-CoV, demonstrating broad-spectrum potential. Our findings highlight CRISPR-Cas13b as a promising tool for antiviral therapeutics, underscoring its potential in RNA-virus-associated pandemic responses. Full article

Collaboration among road agents, such as connected autonomous vehicles and roadside units, enhances driving performance by enabling the exchange of valuable information. However, existing collaboration methods predominantly focus on perception tasks and rely on single-frame static information sharing, which limits the effective exchange of temporal data and hinders broader applications of collaboration. To address this challenge, we propose CoPnP, a novel collaborative joint perception and prediction system, whose core innovation is to realize multi-frame spatial–temporal information sharing. To achieve effective and communication-efficient information sharing, two novel designs are proposed: (1) a task-oriented spatial–temporal information-refinement model, which filters redundant and noisy multi-frame features into concise representations; (2) a spatial–temporal importance-aware feature-fusion model, which comprehensively fuses features from various agents. The proposed CoPnP expands the benefits of collaboration among road agents to the joint perception and prediction task. The experimental results demonstrate that CoPnP outperforms existing state-of-the-art collaboration methods, achieving a significant performance-communication trade-off and yielding up to 11.51%/10.34% Intersection over union and 12.31%/10.96% video panoptic quality gains over single-agent PnP on the OPV2V/V2XSet datasets. Full article

Objectives: To address the poor efficacy and percutaneous penetration of grape seed oil, ionic liquids and nanotechnology were combined to prepare a grape seed oil emulsion. Methods: A novel Menthol-CoQ10 ionic liquid and ionic liquid based grapeseed oil emulsion were prepared and confirmed. Results: The average size of the grapeseed oil emulsion was 218 nm, and its zeta potential was −33.5 mV. The ionic liquid-based grape seed oil emulsion exhibited a transdermal penetration effect 4.63-fold higher than that of ordinary grape seed oil emulsion. Ionic liquid also displayed enhanced efficiency both in vitro and in vivo. It significantly inhibited the production of DPPH free radicals and tyrosinase, inhibited melanin and matrix metalloproteinase-1 (MMP-1) produced by cells, and promoted type I collagen expression in fibroblasts. After 28 days of continuous use, the grapeseed oil emulsion improved the water content of the stratum corneum and the rate of transepidermal water loss, enhanced the firmness and elasticity of the skin, and significantly improved the total number and length of under-eye lines, tail lines, nasolabial folds, and marionette lines on the face. Conclusions: Menthol-CoQ10 ionic liquid is a promising functional excipient for both transdermal delivery increase and efficient enhancement. Ionic liquid and nanotechnology for grape seed oil facial mask displayed significantly enhanced efficacy and permeability. Full article

The electrochemical hydrogen evolution reaction (HER) was considered to be a promising strategy for future clean energy. In this work, a composite electrocatalyst (designated as CGO36@CC) was synthesized through anchoring of nano spinel structure Co₂GeO₄ onto carbon cloth fibers and exhibited outstanding electrocatalytic performance for HERs in an alkaline medium. The characterization outcome established that, after 36 h of hydrothermal reaction, nano spinel structure Co₂GeO₄ particles (exposed abundant 111 crystal planes) were stably loaded onto a carbon cloth fiber surface, and this structural configuration facilitated the electrons transferring between each other. In addition, the electrochemical analysis revealed that the incorporation of nano spinel structure Co₂GeO₄ and carbon cloth significantly augmented the electrochemical activity value of the composite and efficiently enhanced the HER performance. Notably, the overpotential was merely 96 mV at 10 mA·cm⁻² current density, and the Tafel slope was only 48.9 mV·dec⁻¹. Moreover, CGO36@CC displayed remarkable catalytic activity and sustained HER catalytic stability. The theoretical catalytic prowess of CGO36@CC stemmed from the collaborative influence of germanium and cobalt atoms within the exposed 111 crystal plane of the Co₂GeO₄ molecular framework. The amalgamation of Co₂GeO₄ with carbon cloth fiber conferred upon the composite electrocatalyst both superior theoretical catalytic activity and enhanced electron transfer capability. This work provides a novel strategy for exploring a highly efficient composite electrocatalyst combined transition metal with carbon material to accelerate the HER activity. Full article

Objectives: Currently available research data points to COVID-19-related multi-organ system damage. This study aims to evaluate the impact of SARS-CoV-2 on the reproductive health, that is, plasma levels of FSH, LH, estradiol, AMH, and antral follicular count, of women undergoing level II ART techniques. Methods: This is a multicenter, prospective, and observational study by the reproductive medicine centers of Palermo’s Ospedali Riuniti Villa Sofia-Cervello Hospital and Vanvitelli University. From September 2022 to March 2024, 203 patients aged 24–43 were enrolled, all with diagnosed infertility and a history of SARS-CoV-2 infection. Symptomatic women, patients testing positive for HIV or other liver viruses, and patients with a history of ovarian cancer or who had taken gonadotoxic drugs were excluded. Plasma measurements of FSH, LH, estradiol, AMH, and antral follicular count were performed before and after infection. Results: The analysis accounting for the concentration of anti-Müllerian hormone (AMH) before and after COVID-19 infection shows an average concentration decrease from 1.33 ng/mL before SARS-CoV-2 infection to 0.97 ng/mL after infection. Average decrease after infection was −27.4%; average reduction of 1 follicle (95% CI: from −0.74 to −1.33) was reported following SARS-CoV-2 infection. Levels of E2 before and after SARS-CoV-2 infection did not vary significantly. Average FSH and LH levels before and after SARS-CoV-2 infection pointed to an increase. Conclusions: SARS-CoV-2 infection damages female reproductive health, causing significant reductions in AMH (−27.4%) and AFC (−1 antral follicle) values and an increase in FSH (+13.6%) and LH (+13.4%) values. No effect on E2 levels was reported. The pandemic has also affected the ability of infertile patients to access ART procedures, and that calls for a novel, updated blueprint designed to enhance our preparedness in the event that similar circumstances should occur again. Full article

SARS-CoV-2 is a spherical, positive-sense, single-stranded RNA virus with a large genome, responsible for encoding both structural proteins, vital for the viral particle’s architecture, and non-structural proteins, critical for the virus’s replication cycle. Among the non-structural proteins, two cysteine proteases emerge as promising molecular targets for the design of new antiviral compounds. The main protease (M^pro) is a homodimeric enzyme that plays a pivotal role in the formation of the viral replication–transcription complex, associated with the papain-like protease (PL^pro), a cysteine protease that modulates host immune signaling by reversing post-translational modifications of ubiquitin and interferon-stimulated gene 15 (ISG15) in host cells. Due to the importance of these molecular targets for the design and development of novel anti-SARS-CoV-2 drugs, the purpose of this review is to address aspects related to the structure, mechanism of action and strategies for the design of inhibitors capable of targeting the M^pro and PL^pro. Examples of covalent and non-covalent inhibitors that are currently being evaluated in preclinical and clinical studies or already approved for therapy will be also discussed to show the advances in medicinal chemistry in the search for new molecules to treat COVID-19. Full article

While approved vaccines for COVID-19 provide protection against severe disease and death, they have limited efficacy in the prevention of infection and virus transmission. Mucosal immunity is preferred over systemic immunity to provide protection at the point of entry against pathogens such as SARS-CoV-2. VaxForm has developed an oral vaccine delivery platform that elicits mucosal and systemic immune responses by targeting immune cells in the gut through C-type lectin receptors. The technology consists of microencapsulating the vaccine with an enteric polymer, which also results in enhanced thermostability. This article describes the formulation development and in vivo testing of a novel protein-based oral COVID-19 vaccine using this technology. Results demonstrate successful induction of immune response in mice and showed that the particle size of the vaccines following administration can impact the ratio of mucosal to systemic response. Immunogenicity and thermostability of liquid suspension and dry powder versions of the vaccine were compared in mice. The liquid suspension vaccine showed excellent heat resistance by maintaining immunogenicity after 14 days of storage at 60 °C. While further investigation is needed to determine correlates of protection and duration of response for mucosal immunity, this study demonstrates the vaccine’s potential as a COVID-19 booster to enhance mucosal protection in humans and improve global access by lowering the cost of production, removing cold-chain requirements, and allowing self-administration. Full article

The COVID-19 pandemic is caused by a novel and rapidly mutating coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Although several drugs are already in clinical use or under emergency authorization, there is still an urgent need to develop new drugs. Through the mining and analysis of 2776 genomes of the SARS-CoV-2 virus, we identified papain-like protease (PLpro), which is a critical enzyme required for coronavirus to generate a functional replicase complex and manipulate post-translational modifications on host proteins for evasion against host antiviral immune responses, as a conserved molecular target for the development of anti-SARS-CoV-2 therapy. We then made an infection model using the NCI-H1299 cell line stably expressing SARS-CoV-2 PLpro protein (NCI-H1299/PLpro). To investigate the effect of targeting and degrading PLpro mRNA, a compact CRISPR-Cas13 system targeting PLpro mRNA was developed and validated, which was then delivered to the aforementioned NCI-H1299/PLpro cells. The results showed that CRISPR-Cas13 mediated mRNA degradation successfully reduced the expression of viral PLpro protein. By combining the power of AAV and CRISPR-Cas13 technologies, we aim to explore the potential of attenuating viral infection by targeted degradation of important viral mRNAs via safe and efficient delivery of AAV carrying the CRISPR-Cas13 system. This study demonstrated a virus-against-virus gene therapy strategy for COVID-19 and provided evidence for the future development of therapies against SARS-CoV-2 and other RNA viral infections. Full article

The COVID-19 pandemic, instigated by the emergence of the novel coronavirus, SARS-CoV-2, created an incomparable global health crisis. Due to its highly virulent nature, identifying potential therapeutic agents against this lethal virus is crucial. PLpro is a key protein involved in viral polyprotein processing and immune system evasion, making it a prime target for the development of antiviral drugs to combat COVID-19. To expedite the search for potential therapeutic candidates, this review delved into computational studies. Recent investigations have harnessed computational methods to identify promising inhibitors targeting PLpro, aiming to suppress the viral activity. Molecular docking techniques were employed by researchers to explore the binding sites for antiviral drugs within the catalytic region of PLpro. The review elucidates the functional and structural properties of SARS-CoV-2 PLpro, underscoring its significance in viral pathogenicity and replication. Through comprehensive all-atom molecular dynamics (MD) simulations, the stability of drug–PLpro complexes was assessed, providing dynamic insights into their interactions. By evaluating binding energy estimates from MD simulations, stable drug–PLpro complexes with potential antiviral properties were identified. This review offers a comprehensive overview of the potential drug/lead candidates discovered thus far against PLpro using diverse in silico methodologies, encompassing drug repurposing, structure-based, and ligand-based virtual screenings. Additionally, the identified drugs are listed based on their chemical structures and meticulously examined according to various structural parameters, such as the estimated binding free energy (ΔG), types of intermolecular interactions, and structural stability of PLpro–ligand complexes, as determined from the outcomes of the MD simulations. Underscoring the pivotal role of targeting SARS-CoV-2 PLpro in the battle against COVID-19, this review establishes a robust foundation for identifying promising antiviral drug candidates by integrating molecular dynamics simulations, structural modeling, and computational insights. The continual imperative for the improvement of existing drugs and exploring novel compounds remains paramount in the global efforts to combat COVID-19. The evolution and management of COVID-19 hinge on the symbiotic relationship between computational insights and experimental validation, underscoring the interdisciplinary synergy crucial to this endeavor. Full article