Lightweight Biobased Polyurethane Composites Derived from Liquefied Polyol Reinforced by Biomass Sources with High Mechanical Property and Enhanced Fire-Resistance Performance

Lightweight biobased insulation polyurethane (BPU) composite foams with high fire-resistance efficiency are interested in building effective energy and low environmental impact today. This study focuses on manufacturing lightweight BPU from liquefied bamboo polyols and biomass resources, including rice husk and wood flour. Then, they are combined with three flame retardant (FR) additives, such as aluminum diethyl phosphinate, aluminum trihydroxide, and diammonium phosphate, to improve their fire resistance performance. The physicochemical properties, microstructure, thermal stability, mechanical properties, and flame-retardant properties of the BPU composites are characterized to optimize their compromise properties. The results showed that composites with optimized FRs achieved UL94 V-0 and those with nonoptimized FRs reached UL94 HB. The limiting oxygen index exhibited that the fire resistance of BPU composites could increase up to 21-37% within FR additives. In addition, the thermal stability of BPU composites was significantly improved in a temperature range of 300-700 °C and the compressive strength of the BPU composites was also enhanced with the presence of FRs. The scanning electron microscopy observation showed an influence of FRs on the morphology and cell size of the BPU composites. The bio-PU-derived samples in this study showed significantly low thermal conductivity values, demonstrating their remarkable thermal insulation effectiveness.

SARS-CoV-2 Omicron Subvariants Do Not Differ Much in Binding Affinity to Human ACE2: A Molecular Dynamics Study

The emergence of the variant of concern Omicron (B.1.1.529) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) exacerbates the COVID-19 pandemic due to its high contagious ability. Studies have shown that the Omicron binds human ACE2 more strongly than the wild type. The prevalence of Omicron in new cases of COVID-19 promotes novel lineages with improved receptor binding affinity and immune evasion. To shed light on this open problem, in this work, we investigated the binding free energy of the receptor binding domain of the Omicron lineages BA.2, BA.2.3.20, BA.3, BA4/BA5, BA.2.75, BA.2.75.2, BA.4.6, XBB.1, XBB.1.5, BJ.1, BN.1, BQ.1.1, and CH.1.1 to human ACE2 using all-atom molecular dynamics simulation and the molecular mechanics Poisson-Boltzmann surface area method. The results show that these lineages have increased binding affinity compared to the BA.1 lineage, and BA.2.75 and BA.2.75.2 subvariants bind ACE2 more strongly than others. However, in general, the binding affinities of the Omicron lineages do not differ significantly from each other. The electrostatic force dominates over the van der Waals force in the interaction between Omicron lineages and human cells. Based on our results, we argue that viral evolution does not further improve the affinity of SARS-CoV-2 for ACE2 but may increase immune evasion.

Staining-Enhanced Peroxidase-Mimicking Gold Nanoparticles in Nano-ELISA for Highly Sensitive Detection of Klebsiella pneumoniae

Klebsiella pneumoniae, a member of the family Enterobacteriaceae, is a rod-shaped, Gram-negative bacterium, mainly found in the hospital environment and medical tools. It is the leading cause of nosocomial infection, characterized by bloodstream infection, wound site infection, urinary tract infection, and sepsis, mostly in older adults, newborn infants, and immunocompromised patients. This present study demonstrated a novel diagnostic method for K. pneumoniae detection based on the gold nanozyme activity for the oxidation of 3,3',5,5'-tetramethylbenzidine (TMB) in the presence of H2O2. The nanozyme activity of AuNPs with staining enhancement was statistically three times higher than that of the bare AuNPs in solid absorption at 650 nm. Nano-ELISA with staining enhancement could detect as low as 102 CFUs/mL of K. pneumoniae concentration, as the cutoff value was determined to be 0.158, which boosted the sensitivity of the immunoreactions by up to 100-fold. The detection limit of our assays was 26.023 CFUs/mL, and the limit of quantification was 78.857 CFUs/mL. There was no cross-reaction against other bacteria, which proved the immunoassays' remarkable specificity for recognizing K. pneumoniae. Taken together, we successfully developed and optimized the highly sensitive and decently specific nano-ELISA strategy that might be applicable for detecting various other bacterial pathogens.

Binding Mechanism and Surface-Enhanced Raman Scattering of the Antimicrobial Sulfathiazole on Gold Nanoparticles

A combined study using the surface-enhanced Raman scattering (SERS) technique and quantum chemical calculations was carried out to elucidate the adsorption behavior of sulfathiazole, an antibiotic drug, on gold nanoparticles. The tetrahedral Au20 cluster was used as a simple model to mimic a nanostructured gold surface. Computations using density functional theory with the PBE functional were performed in both the gas phase and aqueous medium using a continuum model. The drug is found to bind to the Au metals via the nitrogen of the thiazole ring. The interaction is also partially stabilized by the ring-surface π coupling rather than a sideway adsorption as previously proposed. In an aqueous solution, the drug molecule mainly exists as a deprotonated form, which gives rise to a much greater affinity toward Au nanoparticles as compared to the neutral forms. The drug adsorption further induces a significant alteration on the energy gap of the gold cluster Aun, which could result in an electrical noise. Notable SERS signals below 1600 cm-1, which result from a coupling of several vibrations including the ring breathing, C-C stretching, and N-H bending, could be employed for both qualitative and quantitative detection and assessment of sulfathiazole at trace concentrations.

Durian Shell-Mediated Simple Green Synthesis of Nanocopper against Plant Pathogenic Fungi

The synthesis of fungicides in eco-friendly and cost-effective ways is significantly essential for agriculture. Plant pathogenic fungi cause many ecological and economic issues worldwide, which must be treated with effective fungicides. Here, this study proposes the biosynthesis of fungicides, which combines copper and Cu₂O nanoparticles (Cu/Cu₂O) synthesized using durian shell (DS) extract as a reducing agent in aqueous media. Sugar and polyphenol compounds contained in DS, as the main phytochemicals acting in the reduction procedure, were extracted under different temperatures and duration conditions to obtain the highest yields. We confirmed the extraction process performed at 70 °C for 60 min to be the most effective in extracting sugar (6.1 g/L) and polyphenols (22.7 mg/L). We determined the suitable conditions for Cu/Cu₂O synthesis using a DS extract as a reducing agent for a synthesis time of 90 min, a volume ratio of DR extract/Cu²⁺ of 15:35, an initial pH solution of 10, a synthesis temperature of 70 °C, and a CuSO₄ concentration of 10 mM. The characterization results of as-prepared Cu/Cu₂O NP showed a highly crystalline structure of Cu₂O and Cu with sizes estimated in the range of 40-25 nm and 25-30 nm, respectively. Through in vitro experiments, the antifungal efficacy of Cu/Cu₂O against Corynespora cassiicola and Neoscytalidium dimidiatum was investigated by the inhibition zone. The green-synthesized Cu/Cu₂O nanocomposites, which are potential antifungals against plant pathogens, exhibited excellent antifungal efficacy against both Corynespora cassiicola (MIC = 0.25 g/L, the diameter of the inhibition zone was 22.00 ± 0.52 mm) and Neoscytalidium dimidiatum (MIC = 0.0625 g/L, the diameter of the inhibition zone was 18.00 ± 0.58 mm). Cu/Cu₂O nanocomosites prepared in this study could be a valuable suggestion for the control of plant pathogenic fungi affecting crop species globally.

Identifying Transcription Factors That Prefer Binding to Methylated DNA Using Reduced G-Gap Dipeptide Composition

Transcription factors (TFs) play an important role in gene expression and regulation of 3D genome conformation. TFs have ability to bind to specific DNA fragments called enhancers and promoters. Some TFs bind to promoter DNA fragments which are near the transcription initiation site and form complexes that allow polymerase enzymes to bind to initiate transcription. Previous studies showed that methylated DNAs had ability to inhibit and prevent TFs from binding to DNA fragments. However, recent studies have found that there were TFs that could bind to methylated DNA fragments. The identification of these TFs is an important steppingstone to a better understanding of cellular gene expression mechanisms. However, as experimental methods are often time-consuming and labor-intensive, developing computational methods is essential. In this study, we propose two machine learning methods for two problems: (1) identifying TFs and (2) identifying TFs that prefer binding to methylated DNA targets (TFPMs). For the TF identification problem, the proposed method uses the position-specific scoring matrix for data representation and a deep convolutional neural network for modeling. This method achieved 90.56% sensitivity, 83.96% specificity, and an area under the receiver operating characteristic curve (AUC) of 0.9596 on an independent test set. For the TFPM identification problem, we propose to use the reduced g-gap dipeptide composition for data representation and the support vector machine algorithm for modeling. This method achieved 82.61% sensitivity, 64.86% specificity, and an AUC of 0.8486 on another independent test set. These results are higher than those of other studies on the same problems.

SARS-CoV-2 Omicron Variant Binds to Human Cells More Strongly than the Wild Type: Evidence from Molecular Dynamics Simulation

The emergence of the variant of concern Omicron (B.1.1.529) of the severe acute respiratory syndrome coronavirus 2 has aggravated the Covid-19 pandemic due to its very contagious ability. The high infection rate may be due to the high binding affinity of Omicron to human cells, but both experimental and computational studies have yielded conflicting results on this issue. Some studies have shown that the Omicron variant binds to human angiotensin-converting enzyme 2 (hACE2) more strongly than the wild type (WT), but other studies have reported comparable binding affinities. To shed light on this open problem, in this work, we calculated the binding free energy of the receptor binding domain (RBD) of the WT and Omicron spike protein to hACE2 using all-atom molecular dynamics simulation and the molecular mechanics Poisson-Boltzmann surface area method. We showed that Omicron binds to human cells more strongly than the WT due to increased RBD charge, which enhances electrostatic interaction with negatively charged hACE2. N440K, T478K, E484A, Q493R, and Q498R mutations in the RBD have been found to play a critical role in the stability of the RBD-hACE2 complex. The effect of homogeneous and heterogeneous models of glycans coating the viral RBD and the peptidyl domain of hACE2 was examined. Although the total binding free energy is not sensitive to the glycan model, the distribution of per-residue interaction energies depends on it. In addition, glycans have a little effect on the binding affinity of the WT RBD to hACE2.

A New Pathway for the Preparation of Pyrano[2,3-c]pyrazoles and molecular Docking as Inhibitors of p38 MAP Kinase

We report a new pathway to synthesize pyrano[2,3-c]pyrazoles and their binding mode to p38 MAP kinase. Pyrano[2,3-c]pyrazole derivatives have been prepared through a four-component reaction of benzyl alcohols, ethyl acetoacetate, phenylhydrazine, and malononitrile in the presence of sulfonated amorphous carbon and eosin Y as catalysts. All products were characterized by melting point, ¹H and ¹³C NMR, and HRMS (ESI). The products were screened in silico for their binding activities to both the ATP-binding pocket and the lipid-binding pocket of p38 MAP kinase, using a structure-based flexible docking provided by the engine ADFR. The results showed that eight synthesized compounds had a higher affinity to the lipid pocket than to the other target site, which implied potential applications as allosteric inhibitors. Finally, the most biologically active compound, 5, had a binding affinity comparable to those of other proven lipid pocket inhibitors, with affinity to the target pocket reaching -10.9932 kcal/mol, and also had the best binding affinity to the ATP-binding pockets in all of our products. Thus, our research provides a novel pathway for synthesizing pyrano[2,3-c]pyrazoles and bioinformatic evidence for their biological capability to block p38 MAP kinase pockets, which could be useful for developing cancer or immune drugs.