An Extensive Assessment of Network Embedding in PPI Network Alignment

Network alignment is a fundamental task in network analysis. In the biological field, where the protein–protein interaction (PPI) is represented as a graph, network alignment allowed the discovery of underlying biological knowledge such as conserved evolutionary pathways and functionally conserved proteins throughout different species. A recent trend in network science concerns network embedding, i.e., the modelling of nodes in a network as a low-dimensional feature vector. In this survey, we present an overview of current PPI network embedding alignment methods, a comparison among them, and a comparison to classical PPI network alignment algorithms. The results of this comparison highlight that: (i) only five network embeddings for network alignment algorithms have been applied in the biological context, whereas the literature presents several classical network alignment algorithms; (ii) there is a need for developing an evaluation framework that may enable a unified comparison between different algorithms; (iii) the majority of the proposed algorithms perform network embedding through matrix factorization-based techniques; (iv) three out of five algorithms leverage external biological resources, while the remaining two are designed for domain agnostic network alignment and tested on PPI networks; (v) two algorithms out of three are stated to perform multi-network alignment, while the remaining perform pairwise network alignment.     

Inhibition of Bacterial Adhesion and Biofilm Formation by Seed-Derived Ethanol Extracts from Persea americana Mill

The increase in antibiotic resistance demands innovative strategies to combat microorganisms. The current study evaluated the antibacterial and antivirulence effects of ethanol extracts from Persea americana seeds obtained by the Soxhlet (SE) and maceration (MaE) methods. The UHPLC-DAD-QTOF analysis showed mainly the presence of polyphenols and neolignan. Ethanol extracts were not cytotoxic to mammalian cells (CC₅₀ > 500 µg/mL) and displayed a moderate antibacterial activity against Pseudomonas aeruginosa (IC₅₀ = 87 and 187 µg/mL) and Staphylococcus aureus (IC₅₀ = 144 and 159 µg/mL). Interestingly, no antibacterial activity was found against Escherichia coli. SE and MaE extracts were also able to significantly reduce the bacterial adhesion to A549 lung epithelial cells. Additionally, both extracts inhibited the biofilm growth at 24 h and facilitated the release of internal cell components in P. aeruginosa, which might be associated with cell membrane destabilization. Real-time PCR and agarose electrophoresis gel analysis indicated that avocado seed ethanol extracts (64 µg/mL) downregulated virulence-related factors such as mexT and lasA genes. Our results support the potential of bioproducts from P. americana seeds as anti-adhesive and anti-biofilm agents.     

On the electronic energy spectrum of disordered systems

The present paper deals with the investigation of the electronic energy spectrum of a one-dimensional model of monatomic disordered systems with rectangular-well type atomic potentials. First, an equation describing the connection between the wavefunctions at three consecutive atomic sites is derived, the method followed for this purpose being based on the use of well-known “transfer matrix” together with an approach reported earlier by the author. This connection equation is further analysed with the help of continued fraction methods as well as a perturbational approach (first used by Phariseau), and explicit equations, giving allowed electronic energies for various one-dimensional models with small deviations from periodicity, are obtained thereby. It is found in general that, for the types of disorder considered here, a band structure of electronic energies exists; in addition, there appear extra localised energy levels. The treatments involving continued fractions show that such extra energies lie unambiguously within the forbidden regions of the band structure, while the extra energies obtained with the help of perturbational approach, are seen to have the possibility of lying both in the allowed and forbidden regions. With regard to localisation of electronic states, we have found that, for all tratments, the electronic states other than those giving the band structure are localised. As for the band states Phariseau's approach predicts them to be localised, while the continued fraction methods fail to predict whether the band states are localised or not.     

Copper Binding and Oligomerization Studies of the Metal Resistance Determinant CrdA from Helicobacter pylori

Within this research, the CrdA protein from Helicobacter pylori (HpCrdA), a putative copper-binding protein important for the survival of bacterium, was biophysically characterized in a solution, and its binding affinity toward copper was experimentally determined. Incubation of HpCrdA with Cu(II) ions favors the formation of the monomeric species in the solution. The modeled HpCrdA structure shows a conserved methionine-rich region, a potential binding site for Cu(I), as in the structures of similar copper-binding proteins, CopC and PcoC, from Pseudomonas syringae and from Escherichia coli, respectively. Within the conserved amino acid motif, HpCrdA contains two additional methionines and two glutamic acid residues (MMXEMPGMXXMXEM) in comparison to CopC and PcoC but lacks the canonical Cu(II) binding site (two His) since the sequence has no His residues. The methionine-rich site is in a flexible loop and can adopt different geometries for the two copper oxidation states. It could bind copper in both oxidation states (I and II), but with different binding affinities, micromolar was found for Cu(II), and less than nanomolar is proposed for Cu(I). Considering that CrdA is a periplasmic protein involved in chaperoning copper export and delivery in the H. pylori cell and that the affinity of the interaction corresponds to a middle or strong metal–protein interaction depending on the copper oxidation state, we conclude that the interaction also occurs in vivo and is physiologically relevant for H. pylori.     

The Extracts of Polygonum cuspidatum Root and Rhizome Block the Entry of SARS-CoV-2 Wild-Type and Omicron Pseudotyped Viruses via Inhibition of the S-Protein and 3CL Protease

COVID-19, resulting from infection by the SARS-CoV-2 virus, caused a contagious pandemic. Even with the current vaccines, there is still an urgent need to develop effective pharmacological treatments against this deadly disease. Here, we show that the water and ethanol extracts of the root and rhizome of Polygonum cuspidatum (Polygoni Cuspidati Rhizoma et Radix), a common Chinese herbal medicine, blocked the entry of wild-type and the omicron variant of the SARS-CoV-2 pseudotyped virus into fibroblasts or zebrafish larvae, with IC₅₀ values ranging from 0.015 to 0.04 mg/mL. The extracts were shown to inhibit various aspects of the pseudovirus entry, including the interaction between the spike protein (S-protein) and the angiotensin-converting enzyme II (ACE2) receptor, and the 3CL protease activity. Out of the chemical compounds tested in this report, gallic acid, a phytochemical in P. cuspidatum, was shown to have a significant anti-viral effect. Therefore, this might be responsible, at least in part, for the anti-viral efficacy of the herbal extract. Together, our data suggest that the extracts of P. cuspidatum inhibit the entry of wild-type and the omicron variant of SARS-CoV-2, and so they could be considered as potent treatments against COVID-19.     

Forecasting COVID-19 Epidemic Trends by Combining a Neural Network with Rt Estimation

On 31 December 2019, a cluster of pneumonia cases of unknown etiology was reported in Wuhan (China). The cases were declared to be Coronavirus Disease 2019 (COVID-19) by the World Health Organization (WHO). COVID-19 has been defined as SARS Coronavirus 2 (SARS-CoV-2). Some countries, e.g., Italy, France, and the United Kingdom (UK), have been subjected to frequent restrictions for preventing the spread of infection, contrary to other ones, e.g., the United States of America (USA) and Sweden. The restrictions afflicted the evolution of trends with several perturbations that destabilized its normal evolution. Globally, Rt has been used to estimate time-varying reproduction numbers during epidemics. Methods: This paper presents a solution based on Deep Learning (DL) for the analysis and forecasting of epidemic trends in new positive cases of SARS-CoV-2 (COVID-19). It combined a neural network (NN) and an Rt estimation by adjusting the data produced by the output layer of the NN on the related Rt estimation. Results: Tests were performed on datasets related to the following countries: Italy, the USA, France, the UK, and Sweden. Positive case registration was retrieved between 24 February 2020 and 11 January 2022. Tests performed on the Italian dataset showed that our solution reduced the Mean Absolute Percentage Error (MAPE) by 28.44%, 39.36%, 22.96%, 17.93%, 28.10%, and 24.50% compared to other ones with the same configuration but that were based on the LSTM, GRU, RNN, ARIMA (1,0,3), and ARIMA (7,2,4) models, or an NN without applying the Rt as a corrective index. It also reduced MAPE by 17.93%, the Mean Absolute Error (MAE) by 34.37%, and the Root Mean Square Error (RMSE) by 43.76% compared to the same model without the adjustment performed by the Rt. Furthermore, it allowed an average MAPE reduction of 5.37%, 63.10%, 17.84%, and 14.91% on the datasets related to the USA, France, the UK, and Sweden, respectively.     

Kinetics of crystal growth of strontium tungstate from solutions in sodium tungstate melts by continuous cooling

The crystallisation kinetics of strontium tungstate from unstirred saturated solutions in sodium tungstate melts was studied by continuous cooling from initial crystallisation temperatures T₀ = 1000° to 800°C to room temperature at cooling rates R_T = 0.67° to 3.3°C min⁻¹. The main crystal growth was diffusion rate-controlled; the final crystal growth was rate-controlled by the development rate of excess solute concentration. The estimated diffusion rate constant (k_D) values increased with cooling rates and initial crystallisation temperatures. They are higher than the rate constants for diffusion-controlled growth of calcium tungstate from sodium tungstate melts, but very much smaller than those for strontium tungstate from lithium chloride melts.     

Evolution of Artificial Arginine Analogues—Fluorescent Guanidiniocarbonyl-Indoles as Efficient Oxo-Anion Binders

In this article, we present fluorescent guanidiniocarbonyl-indoles as versatile oxo-anion binders. Herein, the guanidiniocarbonyl-indole (GCI) and methoxy-guanidiniocarbonyl-indole (MGCI) were investigated as ethylamides and compared with the well-known guanidiniocarbonyl-pyrrole (GCP) concerning their photophysical properties as well as their binding behavior towards oxo-anions. Hence, a variety of anionic species, such as carboxylates, phosphonates and sulfonates, have been studied regarding their binding properties with GCP, GCI and MGCI using UV-Vis titrations, in combination with the determination of the complex stoichiometry using the Job method. The emission properties were studied in relation to the pH value using fluorescence spectroscopy as well as the determination of the photoluminescence quantum yields (PLQY). Density functional theory (DFT) calculations were undertaken to obtain a better understanding of the ground-lying electronic properties of the investigated oxo-anion binders. Additionally, X-ray diffraction of GCP and GCI was conducted. We found that GCI and MGCI efficiently bind carboxylates, phosphonates and sulfonates in buffered aqueous solution and in a similar range as GCP (K_ass ≈ 1000–18,000 M⁻¹, in bis-tris buffer, pH = 6); thus, they could be regarded as promising emissive oxo-anion binders. They also exhibit a visible fluorescence with a sufficient PLQY. Additionally, the excitation and emission wavelength of MGCI was successfully shifted closer to the visible region of the electromagnetic spectrum by introducing a methoxy-group into the core structure, which makes them interesting for biological applications.     

Characterizing polymer macrostructures by identifying and locating microstructures along their chains with the kerr effect

In this brief report, we demonstrate that Kerr effect measurements, which determine the excess birefringence contributed by polymer solutes in dilute solutions observed under a strong electric field, are highly sensitive to and capable of determining their microstructures, as well as their locations along the macromolecular backbone. Specifically, using atactic triblock copolymers with the same overall composition of styrene (S) and p-bromostyrene (pBrS) units, but with two different block arrangements, that is, pBrS₉₀-b-S₁₂₀-b-pBrS₉₀ (I) and S₆₀-b-pBrS₁₈₀-b-S₆₀ (II), which are indistinguishable by NMR, we detected a dramatic difference in their molar Kerr constants (_mK), in agreement with those previously estimated. Although similar in magnitude, their Kerr constants differ in sign, with _mK(II) positive and _mK(I) negative. In addition, S/pBrS random and gradient copolymers synthesized by reversible addition-fragmentation chain-transfer (RAFT) polymerization exhibit a heretofore unexpected enhanced enchainment of racemic (r) pBrS-pBrS diads. Comparison of their observed and calculated _mKs suggests that the gradient S/pBrS copolymers possess an unanticipated additional gradient in stereosequence that parallels their comonomer gradient, that is, as the concentration of pBrs units decreases from one end of the copolymer chain to the other, so does the content of r diads. This conclusion could only be reached by comparison of observed and calculated Kerr effects, which access the global properties of macromolecules, and not NMR, which is only sensitive to local polymer structural environments, but not to their locations on the copolymer chains. Molar Kerr constants are characteristic of entire polymer chains and are highly sensitive to their constituent microstructures and their distribution along the chain. They may be used to both identify constituent microstructures and locate them along the polymer chain, thereby enabling, for the first time, characterization of their complete macrostructures. © 2013 Wiley Periodicals, Inc. J Polym Sci Part B: Polym Phys, 2013     

Analysis of Malathion and its Breakdown Products in Aquaria Containing Golden Shiners (N. CHRYSOLEUCAS)

Abstract

The 1-ethylmonocarboxylic acid of Malathion (MCA) was identified as a metabolite of Malathion in the gut of golden shiners (N. Chrysoleucas) (7.11 × 10²±0.66 × 10² ng/g tissue). As noted in the literature the rate of hydrolysis of Malathion above pH 7 is first order with respect to Malathion and pH dependent. In addition, the rate of hydrolysis of Malathion in aquaria housing these fish was found to be dependent on the concentration of Ca⁺²; sparging the aquaria with air affected the rate. Some of the hydrolysis products of Malathion were identified by gc/ms and found to be pH dependent above pH 7. The half-life of Malathion under different conditions, the identification of some hydrolytic products and a general scheme for the analysis of Malathion, along with some of its metabolic and hydrolytic products are included in this paper.