Different Impacts of Traffic-Related Air Pollution on Early-Onset and Late-Onset Asthma

Background

Early-onset asthma (EOA) and late-onset asthma (LOA) are two distinct phenotypes. Air pollution has been associated with an increase in poorer asthma outcomes. The objective of this study was to examine the effects of traffic-related air pollution (TRAP) on asthma outcomes in EOA and LOA patients.

Methods

A cross-sectional study was conducted on 675 asthma patients (LOA: 415) recruited from a major medical center in Taiwan. The land-use regression (LUR) model was used to estimate the level of exposure to PM10, PM2.5, NO2, and O3 on an individual level. We investigated the association between TRAP and asthma outcomes in EOA and LOA patients, stratified by allergic sensitization status, using a regression approach.

Results

An increase in PM10 was associated with younger age of onset, increased asthma duration, and decreased lung function in EOA patients (p<0.05). An increase in PM10 was associated with older age of onset, and decreased asthma duration, eosinophil count, and Asthma Control Test (ACT) score in LOA patients. An increase in PM2.5 was associated with younger age of onset, increased asthma duration, decreased eosinophil count, and lung function in EOA patients (p<0.05). An increase in PM2.5 was associated with decreased lung function and ACT score in LOA patients. An increase in NO2 was associated with increased eosinophil count and decreased lung function in EOA patients (p<0.05). An increase in O3 was associated with decreased lung function in LOA patients (p<0.05). In addition, associations of TRAP with age of onset and eosinophil counts were mainly observed in both EOA and LOA patients with allergic sensitization, and an association with ACT was mainly observed in LOA patients without allergic sensitization.

Conclusion

The impact of TRAP on age of onset, eosinophil count, and lung function in EOA patients, and ACT in LOA patients, was affected by the status of allergic sensitization.

Natural compounds inhibit Monkeypox virus methyltransferase VP39 in silico studies

VP39, an essential 2'-O-RNA methyltransferase enzyme discovered in Monkeypox virus (MPXV), plays a vital role in viral RNA replication and transcription. Inhibition of the enzyme may prevent viral replication. In this context, using a combination of molecular docking and molecular dynamics (MDs) simulations, the inhibitory ability of NCI Diversity Set VII natural compounds to VP39 protein was investigated. It should be noted that the computed binding free energy of ligand via molecular docking and linear interaction energy (LIE) approaches are in good agreement with the corresponding experiments with coefficients of R = 0.72 and 0.75, respectively. NSC 319990, NSC 196515 and NSC 376254 compounds were demonstrated that can inhibit MPVX methyltransferase VP39 protein with the similar affinity compared to available inhibitor sinefungin. Moreover, nine residues involving Gln39, Gly68, Gly72, Asp95, Arg97, Val116, Asp138, Arg140 and Asn156 may be argued that they play an important role in binding process of inhibitors to VP39.Communicated by Ramaswamy H. Sarma.

Upgrading nirmatrelvir to inhibit SARS-CoV-2 Mpro via DeepFrag and free energy calculations

The first oral drug for the treatment of COVID-19, Paxlovid, has been authorized; however, nirmatrelvir, a major component of the drug, is reported to be associated with some side effects. Moreover, the appearance of many novel variants raises concerns about drug resistance, and designing new potent inhibitors to prevent viral replication is thus urgent. In this context, using a hybrid approach combining machine learning (ML) and free energy simulations, 6 compounds obtained by modifying nirmatrelvir were proposed to bind strongly to SARS-CoV-2 Mpro. The structural modification of nirmatrelvir significantly enhances the electrostatic interaction free energy between the protein and ligand and slightly decreases the vdW term. However, the vdW term is the most important factor in controlling the ligand-binding affinity. In addition, the modified nirmatrelvir might be less toxic to the human body than the original inhibitor.

Escalating Catalytic Activity for Hydrogen Evolution Reaction on MoSe2@Graphene Functionalization

Developing highly efficient and durable hydrogen evolution reaction (HER) electrocatalysts is crucial for addressing the energy and environmental challenges. Among the 2D-layered chalcogenides, MoSe₂ possesses superior features for HER catalysis. The van der Waals attractions and high surface energy, however, stack the MoSe₂ layers, resulting in a loss of edge active catalytic sites. In addition, MoSe₂ suffers from low intrinsic conductivity and weak electrical contact with active sites. To overcome the issues, this work presents a novel approach, wherein the in situ incorporated diethylene glycol solvent into the interlayers of MoSe₂ during synthesis when treated thermally in an inert atmosphere at 600 °C transformed into graphene (Gr). This widened the interlayer spacing of MoSe₂, thereby exposing more HER active edge sites with high conductivity offered by the incorporated Gr. The resulting MoSe₂-Gr composite exhibited a significantly enhanced HER catalytic activity compared to the pristine MoSe₂ in an acidic medium and demonstrated a superior HER catalytic activity compared to the state-of-the-art Pt/C catalyst, particularly at a high current density beyond ca. 55 mA cm^-2. Additionally, the MoSe₂-Gr catalyst demonstrated long-term electrochemical stability during HER. This work, thus, presents a facile and novel approach for obtaining an efficient MoSe₂ electrocatalyst applicable in green hydrogen production.

Characterizing the ligand-binding affinity toward SARS-CoV-2 Mpro via physics- and knowledge-based approaches

Computational approaches, including physics- and knowledge-based methods, have commonly been used to determine the ligand-binding affinity toward SARS-CoV-2 main protease (Mpro or 3CLpro). Strong binding ligands can thus be suggested as potential inhibitors for blocking the biological activity of the protease. In this context, this paper aims to provide a short review of computational approaches that have recently been applied in the search for inhibitor candidates of Mpro. In particular, molecular docking and molecular dynamics (MD) simulations are usually combined to predict the binding affinity of thousands of compounds. Quantitative structure-activity relationship (QSAR) is the least computationally demanding and therefore can be used for large chemical collections of ligands. However, its accuracy may not be high. Moreover, the quantum mechanics/molecular mechanics (QM/MM) method is most commonly used for covalently binding inhibitors, which also play an important role in inhibiting the activity of SARS-CoV-2. Furthermore, machine learning (ML) models can significantly increase the searching space of ligands with high accuracy for binding affinity prediction. Physical insights into the binding process can then be confirmed via physics-based calculations. Integration of ML models into computational chemistry provides many more benefits and can lead to new therapies sooner.

Correction: Characterizing the ligand-binding affinity toward SARS-CoV-2 Mpro via physics- and knowledge-based approaches

Correction for 'Characterizing the ligand-binding affinity toward SARS-CoV-2 Mpro via physics- and knowledge-based approaches' by Son Tung Ngo et al., Phys. Chem. Chem. Phys., 2022, https://doi.org/10.1039/d2cp04476e.

Correction: Rapid prediction of possible inhibitors for SARS-CoV-2 main protease using docking and FPL simulations

[This corrects the article DOI: 10.1039/D0RA06212J.].

Rotary bi-layer ring-shaped metamaterials for reconfiguration absorbers: publisher's note

This publisher's note corrects errors in Appl. Opt.61, 9078 (2022)APOPAI0003-693510.1364/AO.471949.

Density Functional Study of Size-Dependent Hydrogen Adsorption on Ag n Cr (n = 1-12) Clusters

Increasing interest has been paid for hydrogen adsorption on atomically controlled nanoalloys due to their potential applications in catalytic processes and energy storage. In this work, we investigate the interaction of H₂ with small-sized Ag _n Cr (n = 1-12) using density functional theory calculations. It is found that the cluster structures are preserved during the adsorption of H₂ either molecularly or dissociatively. Ag₃Cr-H₂, Ag₆Cr-H₂, and Ag₉Cr-H₂ clusters are identified to be relatively more stable from computed binding energies and second-order energy difference. The dissociation of adsorbed H₂ on Ag₂Cr, Ag₃Cr, Ag₆Cr, and Ag₇Cr clusters is favored both thermodynamically and kinetically. The dissociative adsorption is unlikely to occur because of a considerable energy barrier before reaching the final state for Ag₄Cr or due to energetic preferences for n = 1, 5, and 8-12 species. Comprehensive analysis shows that the geometric structure of clusters, the relative electronegativity, and the coordination number of the Cr impurity play a decisive role in determining the preferred adsorption configuration.

Rotary bi-layer ring-shaped metamaterials for reconfiguration absorbers

A reconfigurable metamaterial absorber (MA) in the microwave region is numerically and experimentally demonstrated based on a multi-layered metamaterial. The proposed structure can be mechanically switched between two different configurations to obtain designated absorption behaviors. By rotating the upper ring layer by multiples of 90 deg, two separated absorption modes of the MA are created. The first configuration acts as a single-band absorber, while the second configuration performs multi-band perfect absorption. In addition, the proposed structure can be easily switched into two different configurations to obtain a designated absorption feature. Our work is expected to provide an effective approach to obtaining reconfigurable MAs, which are useful for various applications.

A neuro-fuzzy approach for multipoint data prediction in passive clustered wireless sensor networks

In Passive Clustered Wireless Sensor Networks (WSNs), energy is lost in a sensor node during the data transmission. In order to avoid the energy loss due to data transmission, a data prediction technique is implemented. In this paper, we present a new multi-point data prediction technique, in which the prediction algorithm is initially implemented at both member nodes and cluster heads. The algorithm is updated to cluster head by member nodes by tracking temporal correlation of data. Neuro-Fuzzy model is used as a predictor in both member nodes and cluster heads. The simulation is performed using MATLAB and the overall energy in nodes seems to increase. The mean square error (MSE) value is reduced to greater extend.

Dioctyl Phthalate-Modified Graphene Nanoplatelets: An Effective Additive for Enhanced Mechanical Properties of Natural Rubber

Graphene has been extensively considered an ideal additive to improve the mechanical properties of many composite materials, including rubbers, because of its novel strength, high surface area, and remarkable thermal and electron conductivity. However, the pristine graphene shows low dispersibility in the rubber matrix resulting in only slightly enhanced mechanical properties of the rubber composite. In this work, graphene nanoplatelets (GNPs) were modified with dioctyl phthalate (DOP) to improve the dispersibility of the graphene in the natural rubber (NR). The distribution of the DOP-modified GNPs in the NR matrix was investigated using scanning electron microscopy, X-ray diffraction, and Raman spectroscopy. The effect of the modified GNPs’ contents on the mechanical properties of the GNPs/NR composite was studied in detail. The results showed that the abrasion resistance of the graphene-reinforced rubber composite significantly improved by 10 times compared to that of the rubber without graphene (from 0.3 to 0.03 g/cycle without and with addition of the 0.3 phr modified GNPs). The addition of the modified GNPs also improved the shear and tensile strength of the rubber composite. The tensile strength and shear strength of the NR/GNPs composite with a GNPs loading of 0.3 phr were determined to be 23.63 MPa and 42.69 N/mm, respectively. Even the presence of the graphene reduced the other mechanical properties such as Shore hardness, elongation at break, and residual elongation; however, these reductions were negligible, which still makes the modified GNPs significant as an effective additive for the natural rubber in applications requiring high abrasion resistance.

Systematic synthesis of different-sized AgInS2/GaSxnanocrystals for emitting the strong and narrow excitonic luminescence

This paper presents for the first time the systematic synthesis of AgInS₂(AIS) nanocrystals (NCs) with different sizes of 2.6-6.8 nm just by controlling only the reaction temperature. The synthesis of AIS core NCs was carried out in 2 steps: (i) synthesis of Ag₂S NCs and then (ii) partial exchange of Ag⁺with In³⁺in the template Ag₂S NCs. For step (i), Ag₂S NCs of different sizes were synthesized by reaction of the Ag and S precursors at different temperatures of 30 °C to 130 °C, for the same reaction time of 30 min. For step (ii), AIS NCs were created by the exchange of Ag⁺with In³⁺at 120 °C for 60 min. Finally, GaS_xwas shelled on AIS core NCs to produce the AgInS₂/GaS_xcore/shell structures. The synthesized AIS/GaS_xNCs demonstrate the clear excitonic absorptions and strong, narrow excitonic luminescence peaking at 530-606 nm depending on the size of AIS core NCs.

First-row transition metal doped germanium clusters Ge16M: some remarkable superhalogens

A theoretical study of geometric and electronic structures, stability and magnetic properties of both neutral and anionic Ge₁₆M^0/− clusters with M being a first-row 3d transition metal atom, is performed using quantum chemical approaches. Both the isoelectronic Ge₁₆Sc⁻ anion and neutral Ge₁₆Ti that have a perfect Frank–Kasper tetrahedral T_d shape and an electron shell filled with 68 valence electrons, emerge as magic clusters with an enhanced thermodynamic stability. The latter can be rationalized by the simple Jellium model. Geometric distortions from the Frank–Kasper tetrahedron of Ge₁₆M having more or less than 68 valence electrons can be understood by a Jahn–Teller effect. Remarkably, DFT calculations reveal that both neutral Ge₁₆Sc and Ge₁₆Cu can be considered as superhalogens as their electron affinities (≥3.6 eV) exceed the value of the halogen atoms and even that of icosahedral Al₁₃. A detailed view of the magnetic behavior of Ge₁₆M^0/− clusters shows that the magnetic moments of the atomic metals remain large even when they are quenched upon doping. When M goes from Sc to Zn, the total spin magnetic moment of Ge₁₆M^0/− increases steadily and reaches the maximum value of 3 μ_B with M = Mn before decreasing towards the end of the first-row 3d block metals. Furthermore, the IR spectra of some tetrahedral Ge₁₆M are also predicted.

A theoretical study of geometric and electronic structures, stability and magnetic properties of both neutral and anionic Ge₁₆M^0/− clusters with M being a first-row 3d transition metal atom, is performed using quantum chemical approaches.

Insights into the binding and covalent inhibition mechanism of PF-07321332 to SARS-CoV-2 Mpro

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been causing the COVID-19 pandemic, resulting in several million deaths being reported. Numerous investigations have been carried out to discover a compound that can inhibit the biological activity of the SARS-CoV-2 main protease, which is an enzyme related to the viral replication. Among these, PF-07321332 (Nirmatrelvir) is currently under clinical trials for COVID-19 therapy. Therefore, in this work, atomistic and electronic simulations were performed to unravel the binding and covalent inhibition mechanism of the compound to M^pro. Initially, 5 μs of steered-molecular dynamics simulations were carried out to evaluate the ligand-binding process to SARS-CoV-2 M^pro. The successfully generated bound state between the two molecules showed the important role of the PF-07321332 pyrrolidinyl group and the residues Glu166 and Gln189 in the ligand-binding process. Moreover, from the MD-refined structure, quantum mechanics/molecular mechanics (QM/MM) calculations were carried out to unravel the reaction mechanism for the formation of the thioimidate product from SARS-CoV-2 M^pro and the PF-07321332 inhibitor. We found that the catalytic triad Cys145–His41–Asp187 of SARS-CoV-2 M^pro plays an important role in the activation of the PF-07321332 covalent inhibitor, which renders the deprotonation of Cys145 and, thus, facilitates further reaction. Our results are definitely beneficial for a better understanding of the inhibition mechanism and designing new effective inhibitors for SARS-CoV-2 M^pro.

The catalytic triad Cys145–His41–Asp187 of SARS-CoV-2 M^pro plays an important role in the activation of the PF-07321332 covalent inhibitor.

Associations between lung-deposited dose of particulate matter and culture-positive pulmonary tuberculosis pleurisy

Epidemiological studies identified the relationship between air pollution and pulmonary tuberculosis. Effects of lung-deposited dose of particulate matter (PM) on culture-positive pulmonary tuberculosis remain unclear. This study investigates the association between lung-deposited dose of PM and pulmonary tuberculosis pleurisy. A case-control study of subjects undergoing pleural effusion drainage of pulmonary tuberculosis (case) and chronic heart failure (control) was conducted. Metals and biomarkers were quantified in the pleural effusion. The air pollution exposure was measured and PM deposition in the head, tracheobronchial, alveolar region, and total lung region was estimated by Multiple-path Particle Dosimetry (MPPD) Model. We performed multiple logistic regression to examine the associations of these factors with the risk of tuberculosis. We observed that 1-μg/m³ increase in PM₁₀ was associated with 1.226-fold increased crude odds ratio (OR) of tuberculosis (95% confidence interval (CI): 1.023-1.469, p<0.05), 1-μg/m³ increase in PM_2.5-10 was associated with 1.482-fold increased crude OR of tuberculosis (95% CI: 1.048-2.097, p < 0.05), 1-ppb increase in NO₂ was associated with 1.218-fold increased crude OR of tuberculosis (95% CI: 1.025-1.447, p < 0.05), and 1-ppb increase in O₃ was associated with 0.735-fold decreased crude OR of tuberculosis (95% CI: 0.542 0.995). We observed 1-μg/m³ increase in PM deposition in head and nasal region was associated with 1.699-fold increased crude OR of tuberculosis (95% CI: 1.065-2.711, p < 0.05), 1-μg/m³ increase in PM deposition in tracheobronchial region was associated with 1.592-fold increased crude OR of tuberculosis (95% CI: 1.095-2.313, p < 0.05), 1-μg/m³ increase in PM deposition in alveolar region was associated with 3.981-fold increased crude OR of tuberculosis (95% CI: 1.280-12.386, p < 0.05), and 1-μg/m³ increase in PM deposition in total lung was associated with 1.511-fold increased crude OR of tuberculosis (95% CI: 1.050-2.173, p < 0.05). The results indicate that particle deposition in alveolar region could cause higher risk of pulmonary tuberculosis pleurisy than deposition in other lung regions.

Unbinding ligands from SARS-CoV-2 Mpro via umbrella sampling simulations

The umbrella sampling (US) simulation is demonstrated to be an efficient approach for determining the unbinding pathway and binding affinity to the SARS-CoV-2 Mpro of small molecule inhibitors. The accuracy of US is in the same range as the linear interaction energy (LIE) and fast pulling of ligand (FPL) methods. In detail, the correlation coefficient between US and experiments does not differ from FPL and is slightly smaller than LIE. The root mean square error of US simulations is smaller than that of LIE. Moreover, US is better than FPL and poorer than LIE in classifying SARS-CoV-2 Mpro inhibitors owing to the reciever operating characteristic-area under the curve analysis. Furthermore, the US simulations also provide detailed insights on unbinding pathways of ligands from the binding cleft of SARS-CoV-2 Mpro. The residues Cys44, Thr45, Ser46, Leu141, Asn142, Gly143, Glu166, Leu167, Pro168, Ala191, Gln192 and Ala193 probably play an important role in the ligand dissociation. Therefore, substitutions at these points may change the mechanism of binding of inhibitors to SARS-CoV-2 Mpro.

Correction: The binary aluminum scandium clusters Al x Sc y with x + y = 13: when is the icosahedron retained?

Correction for ‘The binary aluminum scandium clusters Al_xSc_y with x + y = 13: when is the icosahedron retained?’ by Ngo Tuan Cuong et al., RSC Adv., 2021, 11, 40072–40084. DOI: 10.1039/D1RA06994B.

Improving ligand-ranking of AutoDock Vina by changing the empirical parameters

AutoDock Vina (Vina) achieved a very high docking-success rate, p ^ , but give a rather low correlation coefficient, R , for binding affinity with respect to experiments. This low correlation can be an obstacle for ranking of ligand-binding affinity, which is the main objective of docking simulations. In this context, we evaluated the dependence of Vina R coefficient upon its empirical parameters. R is affected more by changing the gauss2 and rotation than other terms. The docking-success rate p ^ is sensitive to the alterations of the gauss1, gauss2, repulsion, and hydrogen bond parameters. Based on our benchmarks, the parameter set1 has been suggested to be the most optimal. The testing study over 800 complexes indicated that the modified Vina provided higher correlation with experiment R set 1 = 0.556 ± 0.025 compared with R Default = 0.493 ± 0.028 obtained by the original Vina and R Vina 1.2 = 0.503 ± 0.029 by Vina version 1.2. Besides, the modified Vina can be also applied more widely, giving R ≥ 0.500 for 32/48 targets, compared with the default package, giving R ≥ 0.500 for 31/48 targets. In addition, validation calculations for 1036 complexes obtained from version 2019 of PDBbind refined structures showed that the set1 of parameters gave higher correlation coefficient ( R set 1 = 0.617 ± 0.017 ) than the default package ( R Default = 0.543 ± 0.020 ) and Vina version 1.2 ( R Vina 1.2 = 0.540 ± 0.020 ). The version of Vina with set1 of parameters can be downloaded at https://github.com/sontungngo/mvina. The outcomes would enhance the ranking of ligand-binding affinity using Autodock Vina.

Associations of ambient air pollution with overnight changes in body composition and sleep-related parameters

This study aims to investigate the association of air pollution with overnight change in 4body composition and sleep-related parameters. Body composition of 197 subjects in New Taipei city was measured before and after sleep by bioelectric impedance analysis. Air pollutant data were collected from Taiwan Environmental Protection Administration. Sleep parameters were examined by polysomnography. We observed fine particulate matter (PM_2.5) decreased arterial oxygen saturation (SaO₂) and increased apnea-hypopnea index (AHI); NO₂ increased arousal, AHI, and decreased mean SaO₂; and O₃ inmcreased mean SaO₂. We observed 0.99-μg/m³ increase in PM_2.5 was associated with 18.8% increase in changes of right arm fat percentage (95% confidence interval (CI): 0.004, 0.375) and 0.011-kg increase in changes of right arm fat mass (95% CI: 0.000, 0.021). 2.45-ppb increase in NO₂ was associated with 0.181-kg decrease in changes of muscle mass (95% CI: -0.147, -0.001), 0.192-kg decrease in changes of fat free mass (95% CI: -0.155, -0.001), 21.1% increase in changes of right leg fat percentage (95% CI: 0.012, 0.160), and 21.3% increase in changes of left leg fat percentage (95% CI: 0.006, 0.168). 1.56-ppb increase in O₃ was associated with 29.3% decrease in changes of right leg fat percentage (95% CI: -0.363, -0.013), 0.058-kg increase in changes of right leg fat free mass (95% CI: 0.008, 0.066), and 0.059-kg increase in changes of right leg muscle mass (95% CI: 0.010, 0.066). We observed AHI was associated with overnight changes in fat percentage, total fat mass, muscle mass, bone mass, fat free mass, extracellular water, basal metabolic rate, leg fat percentage, leg fat mass, and trunk fat percentage (p < 0.05). In conclusion, exposure to air pollutants was associated with overnight body composition changes and sleep-related parameters. Nocturnal changes in total muscle mass and leg fat percentage likely contribute to the relationship between air pollution and obstructive sleep apnea.

Association Between Air Pollution and Lung Lobar Emphysema in COPD

The development of emphysema has been linked to air pollution; however, the association of air pollution with the extent of lobar emphysema remains unclear. This study examined the association of particulate matter <2.5 μm in aerodynamic diameters (PM_2.5) (≤2.5 μm), nitrogen dioxide (NO₂), and ozone (O₃) level of exposure with the presence of emphysema in 86 patients with chronic obstructive pulmonary disease (COPD). Exposure to the air pollution estimated using the land-use regression model was associated with lung function, BODE (a body mass index, degree of obstruction, dyspnea severity, and exercise capacity index) quartiles, and emphysema measured as low-attenuation areas on high-resolution CT (HR-CT) lung scans. Using paraseptal emphysema as the reference group, we observed that a 1 ppb increase in O₃ was associated with a 1.798-fold increased crude odds ratio of panlobular emphysema (p < 0.05). We observed that PM_2.5 was associated with BODE quartiles, modified Medical Research Council (mMRC) dyspnea score, and exercise capacity (all p < 0.05). We found that PM_2.5, NO₂, and O₃ were associated with an increased degree of upper lobe emphysema and lower lobe emphysema (all p < 0.05). Furthermore, we observed that an increase in PM_2.5, NO₂, and O₃ was associated with greater increases in upper lobe emphysema than in lower lobe emphysema. In conclusion, exposure to O₃ can be associated with a higher risk of panlobular emphysema than paraseptal emphysema in patients with COPD. Emphysema severity in lung lobes, especially the upper lobes, may be linked to air pollution exposure in COPD.

Loss of E-cadherin due to road dust PM2.5 activates the EGFR in human pharyngeal epithelial cells

Exposure to road dust particulate matter (PM) causes adverse health impacts on the human airway. However, the effects of road dust on the upper airway epithelium in humans remain unclear. We investigated the involvement of the epidermal growth factor receptor (EGFR) after PM with an aerodynamic diameter of < 2.5 μm (PM_2.5)-induced E-cadherin disruption of human pharyngeal epithelial cells. First, we collected road dust PM_2.5 from 10 Chinese cities, including Wuhan, Nanjing, Shanghai, Guangzhou, Chengdu, Beijing, Lanzhou, Tianjin, Harbin, and Xi'an. Human pharyngeal FaDu cells were exposed to road dust PM_2.5 at 50 μg/mL for 24 h, cytotoxicity (cell viability and lactate dehydrogenase (LDH)) was assessed, and expressions of the proinflammatory interleukin (IL)-6 and high-mobility group box 1 (HMGB1) protein, receptor for advanced glycation end products (RAGE), occludin, E-cadherin, EGFR, and phosphorylated (p)-EGFR were determined. The E-cadherin gene was then knocked down to investigate EGFR activation in FaDu cells. Exposure to road dust PM_2.5 resulted in a decrease in cell viability and increases in LDH and IL-6. Our data suggested that PM_2.5 could decrease expressions of occludin and E-cadherin and increase expressions of EGFR and p-EGFR, which was confirmed by E-cadherin-knockdown. Our results showed a negative association between the alterations in E-cadherin and total elemental components in correlation analysis, especially S, Cl, K, Ti, Mn, Fe, Cu, Zn, and Pb. Exposure to metals in PM_2.5 from road dust may lead to loss of the barrier function of the upper airway epithelium and activation of the EGFR. Our study showed the adverse effects of road dust PM_2.5 on pharyngeal epithelial cells of the human upper airway.

Self-Assembly of Porphyrin Nanofibers on ZnO Nanoparticles for the Enhanced Photocatalytic Performance for Organic Dye Degradation

Synthesizing novel photocatalysts that can effectively harvest photon energy over a wide range of the solar spectrum for practical applications is vital. Porphyrin-derived nanostructures with properties similar to those of chlorophyll have emerged as promising candidates to meet this requirement. In this study, tetrakis(4-carboxyphenyl) porphyrin (TCPP) nanofibers were formed on the surface of ZnO nanoparticles using a simple self-assembly approach. The obtained ZnO/TCPP nanofiber composites were characterized via scanning electron microscopy, X-ray diffraction analysis, and ultraviolet-visible absorbance and reflectance measurements. The results demonstrated that the ZnO nanoparticles with an average size of approximately 37 nm were well integrated in the TCPP nanofiber matrix. The resultant composite showed photocatalytic activity of ZnO and TCPP nanofibers concomitantly, with band gap energies of 3.12 and 2.43 eV, respectively. The ZnO/TCPP photocatalyst exhibited remarkable photocatalytic performance for RhB degradation with a removal percentage of 97% after 180 min of irradiation under simulated sunlight because of the synergetic activity of ZnO and TCPP nanofibers. The dominant active species participating in the photocatalytic reaction were •O2 - and OH•, resulting in enhanced charge separation by exciton-coupled charge-transfer processes between the hybrid materials.

Higher alveolar deposition of particulate matter in emphysematous lobes of COPD

Emphysema can be examined quantitatively on high-resolution computed tomography (HRCT) by measuring the low-attenuation areas of the lung and has been associated with decrease in lung function in patients with COPD [1]. Previous studies have associated levels of air pollution with emphysema severity of the total lung [2, 3]. However, the relationship between inhaled particulate matter (PM) deposition in the lungs and the degree of emphysema at the lung lobar level remains poorly understood. We examined the association of lung lobe-deposited doses of PM_2.5 (particles with a 50% cut-off aerodynamic diameter of 2.5 μm) with the extent of emphysema in different lung lobes of COPD subjects.

The novelty of this study is that it identified the associations between PM_2.5 deposition in the lung and the degree of emphysema in different lung lobes of COPD patients, especially in the right middle lobe and both upper lobeshttps://bit.ly/3k21ri0

Recurrence of carcinoma showing thymus-like differentiation (CASTLE) involving the thyroid gland

BACKGROUND

Carcinoma showing thymus-like differentiation (CASTLE) in the thyroid gland is a rare disease with generally a favorable prognosis. Treatment with surgery and adjuvant radiotherapy has been shown to improve local control and long-term survival rates. In this report, we present a case of a recurrent thyroid gland CASTLE and review the literature on the diagnosis and treatment of this disease.

CASE PRESENTATION

A 60-year-old woman, who was diagnosed with a CASTLE thyroid tumor in 2015, had a total thyroidectomy and was maintained on thyroid hormone replacement (levothyroxine). After 5 years, the patient had a recurrence, in an advanced stage unsuitable for surgery. As the patient declined to undergo radiotherapy, she was followed up without intervention and is currently stable after 15 months.

CONCLUSIONS

CASTLE is a rare disease, diagnosed based on postoperative pathology and immunohistochemistry analysis, especially upon CD5 marker. In case of relapse, treatment options include surgery and radiotherapy; however conservative management without intervention is an acceptable alternative in some cases.

Systematic Investigation of the Structure, Stability, and Spin Magnetic Moment of CrM n Clusters (M = Cu, Ag, Au, and n = 2-20) by DFT Calculations

Binary clusters of transition-metal and noble-metal elements have been gathering momentum for not only advanced fundamental understanding but also potential as elementary blocks of novel nanostructured materials. In this regard, the geometries, electronic structures, stability, and magnetic properties of Cr-doped Cu _n , Ag _n , and Au _n clusters (n = 2-20) have been systematically studied by means of density functional theory calculations. It is found that the structural evolutions of CrCu _n and CrAg _n clusters are identical. The icosahedral CrCu₁₂ and CrAg₁₂ are crucial sizes for doped copper and silver species. Small CrAu _n clusters prefer the planar geometries, while the larger ones appear as on the way to establish the tetrahedral CrAu₁₉. Our results show that while each noble atom contributes one s valence electron to the cluster shell, the number of chromium delocalized electrons is strongly size-dependent. The localization and delocalization behavior of 3d orbitals of the chromium decide how they participate in metallic bonding, stabilize the cluster, and give rise to and eventually quench the spin magnetic moment. Moreover, molecular orbital analysis in combination with a qualitative interpretation using the phenomenological shell model is applied to reveal the complex interplay between geometric structure, electronic structure, and magnetic moment of clusters. The finding results are expected to provide greater insight into how a host material electronic structure influences the geometry, stability, and formation of spin magnetic moments in doped systems.

Fuzzy Guided Autonomous Nursing Robot through Wireless Beacon Network

Robotics is one of the most emerging technologies today, and are used in a variety of applications, ranging from complex rocket technology to monitoring of crops in agriculture. Robots can be exceptionally useful in a smart hospital environment provided that they are equipped with improved vision capabilities for detection and avoidance of obstacles present in their path, thus allowing robots to perform their tasks without any disturbance. In the particular case of Autonomous Nursing Robots, major essential issues are effective robot path planning for the delivery of medicines to patients, measuring the patient body parameters through sensors, interacting with and informing the patient, by means of voice-based modules, about the doctors visiting schedule, his/her body parameter details, etc. This paper presents an approach of a complete Autonomous Nursing Robot which supports all the aforementioned tasks. In this paper, we present a new Autonomous Nursing Robot system capable of operating in a smart hospital environment area. The objective of the system is to identify the patient room, perform robot path planning for the delivery of medicines to a patient, and measure the patient body parameters, through a wireless BLE (Bluetooth Low Energy) beacon receiver and the BLE beacon transmitter at the respective patient rooms. Assuming that a wireless beacon is kept at the patient room, the robot follows the beacon's signal, identifies the respective room and delivers the needed medicine to the patient. A new fuzzy controller system which consists of three ultrasonic sensors and one camera is developed to detect the optimal robot path and to avoid the robot collision with stable and moving obstacles. The fuzzy controller effectively detects obstacles in the robot's vicinity and makes proper decisions for avoiding them. The navigation of the robot is implemented on a BLE tag module by using the AOA (Angle of Arrival) method. The robot uses sensors to measure the patient body parameters and updates these data to the hospital patient database system in a private cloud mode. It also makes uses of a Google assistant to interact with the patients. The robotic system was implemented on the Raspberry Pi using Matlab 2018b. The system performance was evaluated on a PC with an Intel Core i5 processor, while the solar power was used to power the system. Several sensors, namely HC-SR04 ultrasonic sensor, Logitech HD 720p image sensor, a temperature sensor and a heart rate sensor are used together with a camera to generate datasets for testing the proposed system. In particular, the system was tested on operations taking place in the context of a private hospital in Tirunelveli, Tamilnadu, India. A detailed comparison is performed, through some performance metrics, such as Correlation, Root Mean Square Error (RMSE), and Mean Absolute Percentage Error (MAPE), against the related works of Deepu et al., Huh and Seo, Chinmayi et al., Alli et al., Xu, Ran et al., and Lee et al. The experimental system validation showed that the fuzzy controller achieves very high accuracy in obstacle detection and avoidance, with a very low computational time for taking directional decisions. Moreover, the experimental results demonstrated that the robotic system achieves superior accuracy in detecting/avoiding obstacles compared to other systems of similar purposes presented in the related works.

Preclinical toxicological evaluation of measles virus vaccine strain in non-human primates: A two-month intravenous study

Introduction: Based on its ability to kill tumor cells, the vaccine strain of the measles virus is used for oncolytic virotherapy. However, the dose required for cancer therapy is much higher than that used for vaccination. Therefore, this study was conducted to evaluate the preclinical toxicology of the vaccine strain of measles virus in monkeys. Methods: 16 healthy Macaca mulata monkeys were randomly divided into four groups, of which one was a control. A preclinical safety evaluation of the vaccine strain of the measles virus was performed, and the three experimental groups were intravenously injected with the strain at doses of 105 TCID50, 106 TCID50 and 107 TCID50 respectively. Results: There were no significant abnormalities in the physical, clinical, haematological, and biochemical parameters following the intravenous injection with measles vaccine at doses of 105 TCID50, 106 TCID50 and 107 TCID50. The vaccine strain of measles virus remained in the plasma until the 30th day and disappeared on the 60th, and it did not persist in the tissues on days 30 and 60 post injection. Measles IgG antibody was negative on days 0, 1, 3, and 8 and was positive on days 15, 30, and 60 post administration of the measles virus. The histopathology of target organs was not affected in all groups on days 30 and 60 post injection. Conclusions: The systematic preclinical safety data of the present study confirms the safety of two months of concentrated measles vaccine administration in the Macaca mulata monkey for clinical trials.

N-Methylation of Amines with Methanol in the Presence of Carbonate Salt Catalyzed by a Metal-Ligand Bifunctional Ruthenium Catalyst [(p-cymene)Ru(2,2'-bpyO)(H2O)]

A ruthenium complex [(p-cymene)Ru(2,2'-bpyO)(H₂O)] was found to be a general and efficient catalyst for the N-methylation of amines with methanol in the presence of carbonate salt. Moreover, a series of sensitive substituents, such as nitro, ester, cyano, and vinyl groups, were tolerated under present conditions. It was confirmed that OH units in the ligand are crucial for the catalytic activity. Notably, this research exhibited the potential of metal-ligand bifunctional ruthenium catalysts for the hydrogen autotransfer process.

Binding of inhibitors to the monomeric and dimeric SARS-CoV-2 Mpro

SARS-CoV-2 rapidly infects millions of people worldwide since December 2019. There is still no effective treatment for the virus, resulting in the death of more than one million patients. Inhibiting the activity of SARS-CoV-2 main protease (Mpro), 3C-like protease (3CLP), is able to block the viral replication and proliferation. In this context, our study has revealed that in silico screening for inhibitors of SARS-CoV-2 Mpro can be reliably done using the monomeric structure of the Mpro instead of the dimeric one. Docking and fast pulling of ligand (FPL) simulations for both monomeric and dimeric forms correlate well with the corresponding experimental binding affinity data of 24 compounds. The obtained results were also confirmed via binding pose and noncovalent contact analyses. Our study results show that it is possible to speed up computer-aided drug design for SARS-CoV-2 Mpro by focusing on the monomeric form instead of the larger dimeric one.

Transient transmission of THz metamaterial antennas by impact ionization in a silicon substrate

The picosecond dynamics of excited charge carriers in the silicon substrate of THz metamaterial antennas was studied at different wavelengths. Time-resolved THz pump-THz probe spectroscopy was performed with light from a tunable free electron laser in the 9.3-16.7 THz frequency range using fluences of 2-12 J/m². Depending on the excitation wavelength with respect to the resonance center, transient transmission increase, decrease, or a combination of both was observed. The transient transmission changes can be explained by local electric field enhancement, which induces impact ionization in the silicon substrate, increasing the local number of charge carriers by several orders of magnitude, and their subsequent diffusion and recombination. The studied metamaterials can be integrated with common semiconductor devices and can potentially be used in sensing applications and THz energy harvesting.

The binary aluminum scandium clusters AlxScy with x + y = 13: when is the icosahedron retained?

Geometrical and electronic structures of the 13-atom clusters Al_xSc_y with x + y = 13, as well as their thermodynamic stabilities were investigated using DFT calculations. Both anionic and neutral isomers of Al_xSc_y were found to retain an icosahedral shape of both Al₁₃ and Sc₁₃ systems in which an Al atom occupies the endohedral central position of the icosahedral cage, irrespective of the number of Al atoms present. Such a phenomenon occurs to maximize the number of stronger Al–Al and Sc–Al bonds instead of the weaker Sc–Sc bonds. NBO analyses were applied to examine their electron configurations and rationalize the large number of open shells and thereby high multiplicities of the mixed clusters having more than three Sc atoms. The SOMOs are the molecular orbitals belonged to the irreducible representations of the symmetry point group of the clusters studied, rather than to the cluster electron shells. Evaluation of the average binding energies showed that the thermodynamic stability of Al_xSc_y clusters is insignificantly altered as the number y goes from 0 to 7 and then steadily decreases when y attains the 7–13 range. Increase of the Sc atom number also reduces the electron affinities of the binary Al_xSc_y clusters, and thus they gradually lose the superhalogen characteristics with respect to the pure Al₁₃.

The icosahedral structure of the Al_xSc_y clusters with x + y = 13.

Thermodynamics and kinetics in antibody resistance of the 501Y.V2 SARS-CoV-2 variant

Understanding the thermodynamics and kinetics of the binding process of an antibody to the SARS-CoV-2 receptor-binding domain (RBD) of the spike protein is very important for the development of COVID-19 vaccines. In particular, it is essential to understand how the binding mechanism may change under the effects of RBD mutations. In this context, we have demonstrated that the South African variant (B1.351 or 501Y.V2) can resist the neutralizing antibody (NAb). Three substitutions in the RBD including K417N, E484K, and N501Y alter the free energy landscape, binding pose, binding free energy, binding kinetics, hydrogen bonding, nonbonded contacts, and unbinding pathway of RBD + NAb complexes. The low binding affinity of NAb to 501Y.V2 RBD confirms the antibody resistance of the South African variant. Moreover, the fragment of NAb + RBD can be used as an affordable model to investigate changes in the binding process between the mutated RBD and antibodies.

Increasing FEL minima of 501Y.V2 RBD + antibody in comparison with the WT RBD systems imply that the complex 501Y.V2 RBD + antibody is more unstable than the WT one.

Particulate matter and SARS-CoV-2: A possible model of COVID-19 transmission

Coronavirus disease 2019 (COVID-19), an acute respiratory disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has rapidly developed into a pandemic throughout the world. This disease is a highly infectious novel coronavirus and can affect people of all ages. Previous reports observed that particulate matter (PM) provided a platform for intermixing with viruses (i.e., influenza). However, the role of PM in SARS-CoV-2 transmission remains unclear. In this paper, we propose that PM plays a direct role as a "carrier" of SARS-CoV-2. SARS-CoV-2 is reported to have a high affinity for the angiotensin-converting enzyme 2 (ACE2) receptor. Indirectly, exposure to PM increases ACE2 expression in the lungs which facilitates SARS-CoV-2 viral adhesion. Thus, the high risk of SARS-CoV-2 in heavily polluted regions can be explained by upregulation of ACE2 caused by PM. PM could be both a direct and indirect transmission model for SARS-CoV-2 infection.

A learning-centred approach to teaching linguistic knowledge: Teachers’ perception of teaching periods 1 and 2(/3) in the new English curriculum for secondary schools in Vietnam

The new curriculum was promulgated at the end of 2018. Therefore, there is a need to investigate how teachers perceive the teaching of linguistic knowledge in addition to skills to develop secondary school learners’ communicative competence. The study was carried out during the three months of July, August and October of 2020 in the three provinces of Kien Giang, Ben Tre and Lam Dong with the participation of 120 teachers from 106 secondary schools. Data were collected in the form of group poster presentations for the first two/three periods in the textbooks for the new curriculum and analyzed according to three aspects of form, meaning and use for linguistic knowledge and their sequence. The findings of the study indicate that the teacher participants have a vague idea about teaching the aspects of linguistic knowledge from a learning-centered approach, do not know their sequence of meaning, form and use, and normally follow the activities and their order in the textbook as the only resort available.

Assessing potential inhibitors of SARS-CoV-2 main protease from available drugs using free energy perturbation simulations

The main protease (Mpro) of the novel coronavirus SARS-CoV-2, which has caused the COVID-19 pandemic, is responsible for the maturation of its key proteins. Thus, inhibiting SARS-CoV-2 Mpro could prevent SARS-CoV-2 from multiplying. Because new inhibitors require thorough validation, repurposing current drugs could help reduce the validation process. Many recent studies used molecular docking to screen large databases for potential inhibitors of SARS-CoV-2 Mpro. However, molecular docking does not consider molecular dynamics and thus can be prone to error. In this work, we developed a protocol using free energy perturbation (FEP) to assess the potential inhibitors of SARS-CoV-2 Mpro. First, we validated both molecular docking and FEP on a set of 11 inhibitors of SARS-CoV-2 Mpro with experimentally determined inhibitory data. The experimentally deduced binding free energy exhibits significantly stronger correlation with that predicted by FEP (R = 0.94 ± 0.04) than with that predicted by molecular docking (R = 0.82 ± 0.08). This result clearly shows that FEP is the most accurate method available to predict the binding affinity of SARS-CoV-2 Mpro + ligand complexes. We subsequently used FEP to validate the top 33 compounds screened with molecular docking from the ZINC15 database. Thirteen of these compounds were predicted to bind strongly to SARS-CoV-2 Mpro, most of which are currently used as drugs for various diseases in humans. Notably, delamanid, an anti-tuberculosis drug, was predicted to inhibit SARS-CoV-2 Mpro in the nanomolar range. Because both COVID-19 and tuberculosis are lung diseases, delamanid has higher probability to be suitable for treating COVID-19 than other predicted compounds. Analysis of the complexes of SARS-CoV-2 Mpro and the top inhibitors revealed the key residues involved in the binding, including the catalytic dyad His14 and Cys145, which is consistent with the structural studies reported recently.

Rapid prediction of possible inhibitors for SARS-CoV-2 main protease using docking and FPL simulations

Originating for the first time in Wuhan, China, the outbreak of SARS-CoV-2 has caused a serious global health issue. An effective treatment for SARS-CoV-2 is still unavailable. Therefore, in this study, we have tried to predict a list of potential inhibitors for SARS-CoV-2 main protease (Mpro) using a combination of molecular docking and fast pulling of ligand (FPL) simulations. The approaches were initially validated over a set of eleven available inhibitors. Both Autodock Vina and FPL calculations produced consistent results with the experiments with correlation coefficients of R Dock = 0.72 ± 0.14 and R W = -0.76 ± 0.10, respectively. The combined approaches were then utilized to predict possible inhibitors that were selected from a ZINC15 sub-database for SARS-CoV-2 Mpro. Twenty compounds were suggested to be able to bind well to SARS-CoV-2 Mpro. Among them, five top-leads are periandrin V, penimocycline, cis-p-Coumaroylcorosolic acid, glycyrrhizin, and uralsaponin B. The obtained results could probably lead to enhance the COVID-19 therapy.

Estimation of the ligand-binding free energy of checkpoint kinase 1 via non-equilibrium MD simulations

Checkpoint kinase 1 (CHK1) is a serine/threonine-protein kinase that is involved in cell cycle regulation in eukaryotes. Inhibition of CHK1 is thus considered as a promising approach in cancer therapy. In this study, the fast pulling of ligand (FPL) process was applied to predict the relative binding affinities of CHK1 inhibitors using non-equilibrium molecular dynamics (MD) simulations. The work of external harmonic forces to pull the ligand out of the binding cavity strongly correlated with the experimental binding affinity of CHK1 inhibitors with the correlation coefficient of R = -0.88 and an overall root mean square error (RMSE) of 0.99 kcal/mol. The data indicate that the FPL method is highly accurate in predicting the relative binding free energies of CHK1 inhibitors with an affordable CPU time. A new set of molecules were designed based on the molecular modeling of interactions between the known inhibitor and CHK1 as inhibitory candidates. Molecular docking and FPL results exhibited that the binding affinities of developed ligands were similar to the known inhibitor in interaction with the catalytic site of CHK1, producing very potential CHK1 inhibitors of that the inhibitory activities should be further evaluated in vitro.

A case study of curriculum development: Backward or forward/central design?

Nowadays universities in Vietnam have begun to update their curricula by adopting a backward design with a focus on students’ learning outcomes to replace the old-fashioned forward model. However, to have a constructive alignment is a problem they have to face. This situation has prompted this case study research in May 2020, intending to examine a curriculum to find out whether it is coherent in terms of its main components – objectives, syllabus, methodology, and evaluation. The findings of the study indicate that for this case, although the curriculum was claimed to be of a backward design with learning outcomes as program objectives, it turned out to follow a forward one with more focus on knowledge transfer than competency development. In particular, as the program learning objectives were still written according to knowledge transmission, it was not constructively aligned with the three main components of syllabus, methodology and evaluation: The syllabi were mainly based on the experience of the experts in the field or syllabus designers, the innovation of the methodology as directed by the university with a shift of focus from the lecturer to learners was still interpreted rigidly and mechanically, and the evaluation of student learning was generally claimed to be criterion-referenced only without any elaboration for each syllabus.

Fine Tuning of the Copper Active Site in Polysaccharide Monooxygenases

Type 2 copper active sites, one of the several important copper active sites in biology, were recently found in the novel superfamily of polysaccharide monooxygenases (PMOs) that cleave recalcitrant polysaccharides via an unprecedented oxidative mechanism. The copper center in PMOs is ligated by the bidentate N-terminal histidine residue and another conserved histidine residue, forming a unique T-shaped core termed as Histidine brace. This core serves as the foundation for diverse structures and electronic properties among PMO families and subfamilies. Understanding of the copper active site in PMOs is limited to the static solid structures obtained with X-ray diffraction (XRD), whereas in several families, the copper center exists as a mixture of species in solution as indicated by electron paramagnetic resonance (EPR) spectroscopy. To obtain further details on the copper active sites in PMOs, we carried out density functional theory calculations and molecular dynamics simulations on MtPMO3* that were previously studied with XRD, EPR, mutagenesis, and activity assays. The results reveal the fine-tuning of the binding of the distal ligands by both proximal and distal H-bond-forming residues. Q167 forms H bonds with the proximal O_Tyr ligand of Y167 and the equatorial aqueous ligand (O_eq). T74 forms a H bond with the distal aqueous ligand (O_dis). Removing these H bonds by mutating Q167 or T74 to alanine results in great fluctuations of the axial ligands. Strengthening the proximal H bonds by mutating Q167 to glutamate confines Y167 to the copper centers. In all mutants, the residence time of O_dis is significantly reduced. Q167A, Q167E, and T74A mutants were previously shown to have a significantly reduced activity. Our results indicate that well-tuned H bonds are required for the activity of PMOs.

Effective estimation of the inhibitor affinity of HIV-1 protease via a modified LIE approach

The inhibition of the Human Immunodeficiency Virus Type 1 Protease (HIV-1 PR) can prevent the synthesis of new viruses. Computer-aided drug design (CADD) would enhance the discovery of new therapies, through which the estimation of ligand-binding affinity is critical to predict the most efficient inhibitor. A time-consuming binding free energy method would reduce the usefulness of CADD. The modified linear interaction energy (LIE) approach emerges as an appropriate protocol that performs this task. In particular, the polar interaction free energy, which is obtained via numerically resolving the linear Poisson–Boltzmann equation, plays as an important role in driving the binding mechanism of the HIV-1 PR + inhibitor complex. The electrostatic interaction energy contributes to the attraction between two molecules, but the vdW interaction acts as a repulsive factor between the ligand and the HIV-1 PR. Moreover, the ligands were found to adopt a very strong hydrophobic interaction with the HIV-1 PR. Furthermore, the results obtained corroborate the high accuracy and precision of computational studies with a large correlation coefficient value R = 0.83 and a small RMSE δ_RMSE = 1.25 kcal mol⁻¹. This method is less time-consuming than the other end-point methods, such as the molecular mechanics Poisson–Boltzmann surface area (MM/PBSA) and free energy perturbation (FEP) approaches. Overall, the modified LIE approach would provide ligand-binding affinity with HIV-1 PR accurately, precisely, and rapidly, resulting in a more efficient design of new inhibitors.

The inhibition of the Human Immunodeficiency Virus Type 1 Protease (HIV-1 PR) can prevent the synthesis of new viruses.