Atomic spectrometry update: review of advances in the analysis of clinical and biological materials, foods and beverages

This update covers publications from the second half of 2021 to the middle of 2022. Advances in the application of atomic spectrometry techniques to clinical and biological materials, foods and beverages are reviewed in the text, highlighting their key features. Technical details of sample collection and preparation, as well as progresses with analytical techniques are considered and three tables complement the text, summarising details of a larger spectrum of publications. During this period, the trend toward the application of multi-element techniques, such as EDXRFS, ICP-MS and LIBS continued, in particular for food authenticity studies. Triple quadrupole ICP-MS is becoming increasing popular, as it is less affected by interferences, as well as LIBS and XRF, that require minimal sample preparation. However, AAS is still considered a valid alternative for single or a limited number of elements: as in previous years, numerous pre-concentration techniques were presented, some of which explored "greener” reagents. The interest in NPs continued, both as a potential exposure risk and for their application as tags of biological materials, and led to a wider application of spICP-MS. Chromium speciation in food received more attention than usual during this period, providing evidence that the carcinogenic species CrVI was not present. A number of studies covered the application of atomic spectrometry techniques for the indirect determination of biological macromolecules, including an interesting application of LIBS for the rapid detection of the immune response to SARS-CoV-2. © 2023 The Royal Society of Chemistry.

Complex of Ceftriaxone with Mg(II): Synthesis, Structure, Spectral and Antibacterial Properties

Аннотация. Получен и охарактеризован магниевый комплекс цефтриаксона методами атомно-эмиссионного и элементного анализов, ТГА, ИК- и КР-спектроскопии, РФА и расчетов теории функционала плотности. Цефтриаксон координируется к иону магния через кислород триазинового цикла в шестом положении, азот аминогруппы тиазольного цикла и атомы кислорода карбоксильной и лактамной групп. Динатриевая соль цефтриаксона и комплекс магния были исследованы на антибактериальную активность в отношении Staphylococcus aureus, Escherichia coli и Pseudomonas aeruginosa.Alternate abstract:Magnesium complex of ceftriaxone was obtained and characterized by atomic-emission and elemental analysis, TGA, FTIR and Raman spectroscopy, X-ray diffraction and density functional theory calculations. Ceftriaxone was coordinated to the magnesium ion by the oxygen of the triazine cycle in the 6th position, the nitrogen of the amine group of the thiazole ring, and oxygen atoms of the lactam carbonyl and carboxylate groups. The disodium salt of ceftriaxone and magnesium complex were screened for antibacterial activity against Staphylococcus aureus, Escherichia coli and Pseudomonas aeruginosa.

4-(4-methoxyphenyl)-6-methyl-3-phenyl-4H-1,2,4-oxadiazin-5(6H)-one: Synthesis, crystal structure, Hirshfeld surface analysis, noncovalent, ADMET studies and biological evaluation

Oxadiazines are heterocyclic compounds containing two nitrogen and one oxygen atom in a six-membered ring. The synthesis and crystal structure of 4-(4-methoxyphenyl)-6-methyl-3-phenyl-4H-1,2,4-oxadiazin-5(6H)-one (MPMP-OXA) was reported. The organic crystal structure of the synthesized compound was fully characterized by various spectroscopic techniques (Fourier Transform Infrared Spectroscopy, NMR and LC/MS-TOF) and single-crystal X-ray diffraction studies. The MPMP-OXA crystal structure crystallizes in the triclinic system and space group P-1 with a = 5.9395(15) Å, b = 11.471(3) Å, c = 11.901(3) Å, α = 70.075(4)°, β = 83.454(4)°, γ = 78.016(4)°, V = 744.9(3) Å3, Z = 2 cell parameters. This work is aimed to study the weak interactions in the crystal packing of a new synthesized oxadiazine derivate. The contributions of the most important intermolecular interactions in the crystal structure were investigated by 3D-Hirshfeld surface (HS) and 2D-fingerprint analysis. The C[sbnd]H···O interactions as the most important contributors to the crystal packing between the oxygen of the oxadiazine ring and the hydrogen atom of phenyl ring appear as bright red spots visible on the HS surface. The hydrogen-bonded interaction of MPMP-OXA has been investigated using noncovalent interactions approach. The molecular docking studies for the synthesized compound were performed to gain insight into the inhibition nature of this molecule against DNA Gyrase B Candida and 3-chymotrypsin-like protease (SARS-CoV main protease) proteins and resulted in good activities for new anti-agents. Lastly, Bioavailability, druggability as well as absorption, distribution, metabolism, excretion, and toxicity parameters (ADMET), and gastrointestinal absorption (BOILED-Egg method) properties of newly synthesized compound using smile codes were performed in detail. © 2023 Elsevier B.V.

Advances and critical assessment of machine learning techniques for prediction of docking scores

Here we present three distinct machine learning (ML) approaches (TensorFlow, XGBoost, and SchNetPack) for docking score prediction. AutoDock Vina is used to evaluate the inhibitory potential of ZINC15 in-vivo and in-vitro-only sets towards the SARS-CoV-2 main protease. The in-vivo set (59 884 compounds) is used for ML training (max. 80%), validation (5%), and testing (15%). The in-vitro-only set (174 014 compounds) is used for the evaluation of prediction capability of the trained ML models. Contributions to the prediction error are analyzed with respect to compounds' charge, number of atoms, and expected inhibitory potential (docking score). Methods for the prediction error estimation of new compounds are considered, yet critically rejected. The ML input weighted with respect to the desired property (i.e., low docking score) in the machine learning models shows to be a promising option to improve the ML performance. Proposed models provide significant reduction in number of intriguing compounds that need to be investigated. © 2023 Wiley Periodicals LLC.

Towards De Novo Drug Design for the Coronavirus: A Drug-Target Interaction Prediction Approach using Atom-enhanced Graph Neural Network with Multi-hop Gating Mechanism

For humans, the COVID-19 pandemic and Coronavirus have undeniably been a nightmare. Although there are effective vaccines, specific drugs are still urgent. Normally, to identify potential drugs, one needs to design and then test interactions between the drug and the virus in an in silico manner for determining candidates. This Drug-Target Interaction (DTI) process, can be done by molecular docking, which is too complicated and time-consuming for manual works. Therefore, it opens room for applying Artificial Intelligence (AI) techniques. In particular, Graph Neural Network (GNN) attracts recent attention since its high suitability for the nature of drug compounds and virus proteins. However, to introduce such a representation well-reflecting biological structures of biological compounds is not a trivial task. Moreover, since available datasets of Coronavirus are still not highly popular, the recently developed GNNs have been suffering from overfitting on them. We then address those issues by proposing a novel model known as Atom-enhanced Graph Neural Network with Multi-hop Gating Mechanism. On one hand, our model can learn more precise features of compounds and proteins. On the other hand, we introduce a new gating mechanism to create better atom representation from non-neighbor information. Once applying transfer learning from very large databanks, our model enjoys promising performance, especially when experimenting with Coronavirus. © 2022 IEEE.

Computational study of some potential inhibitors of COVID-19: A DFT analysis

Background: There is an urgent demand of drug or therapy to control the COVID-19. Until July 22, 2021 the worldwide total number of cases reported is more than 192 million and the total number of deaths reported is more than 4.12 million. Several countries have given emergency permission for use of repurposed drugs for the treatment of COVID-19 patients. This report presents a computational analysis on repurposing drugs-tenofovir, bepotastine, epirubicin, epoprostenol, tirazavirin, aprepitant and valrubicin, which can be potential inhibitors of the COVID-19.Method: Density functional theory (DFT) technique is applied for computation of these repurposed drug. For geometry optimization, functional B3LYP/6-311G (d, p) is selected within DFT framework.Results: DFT based descriptors-highest occupied molecular orbital (HOMO)-lowest unoccupied molecular orbital (LUMO) gap, molecular hardness, softness, electronegativity, electrophilicity index, nucleophilicity index and dipole moment of these species are computed. IR and Raman activities are also analysed and studied. The result shows that the HOMO-LUMO gap of these species varies from 1.061 eV to 5.327 eV. Compound aprepitant with a HOMO-LUMO gap of 1.419 eV shows the maximum intensity of IR (786.176 km mol-1) and Raman spectra (15036.702 a.u.).Conclusion: Some potential inhibitors of COVID-19 are studied by using DFT technique. This study shows that epirubicin is the most reactive compound whereas tenofovir is found to be the most stable. Further analysis and clinical trials of these compounds will provide more insight.

SARS-CoV-2 Antibody Effectiveness Is Influenced by Non-Epitope Mutation/Binding-Induced Denaturation of the Epitope 3D Architecture.

The public health threat from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to intensify with emerging variants of concern (VOC) aiming to render COVID-19 vaccines/infection-induced antibodies redundant. The SARS-CoV-2 spike protein is responsible for receptor binding and infection of host cells making it a legitimate antibody target. Antibodies mostly target epitopes in the receptor binding domain (RBD). Mutations occurring within epitopes influence antibody specificity and function by altering their 3D architecture. However, the mechanisms by which non-epitope mutations in the RBD influence antibody specificity and function remain a mystery. We used Protein Data Bank (PDB) deposited 3D structures for the original, Beta, Delta, BA.1, and BA.2 RBD proteins in complex with either neutralizing antibodies or Angiotensin-Converting Enzyme 2 (ACE2) to elucidate the structural and mechanistic basis for neutralizing antibody evasion driven by non-epitope amino acid substitutions in the RBD. Since the mechanism behind the extensively reported functional discrepancies between the same antibody when used individually and when used in an antibody cocktail is lacking, we explored the structural basis for this inconsistency. Finally, since SARS-CoV-2 antibodies are viral mutagens, we deciphered determinants for antibody-pressured amino acid substitutions. On the one hand, we show that non-epitope mutations in the RBD domain of SARS-CoV-2 VOC influence the formation of hydrogen bonds in the paratope-epitope interface by repositioning RBD amino-acid sidechains (AASCs). This increases the distance between complementary donor/acceptor atoms on paratope and epitope AASCs leading to weaker or the complete prevention of the formation of hydrogen bonds in the paratope-epitope interface. On the other hand, we show that SARS-CoV-2 VOC employ the same strategy to simultaneously search for complementary donor/acceptor atoms on ACE2 AASCs to form new interactions, potentially favoring increased viral transmission. Additionally, we illustrate that converting the spike protein to an RBD, a deletion mutation, also repositions epitope AASCs and that AASC interactions in the paratope-epitope interface vary when an antibody is used individually versus when utilized as a cocktail with other antibodies. Finally, we show that the process of substituting immunogenic RBD amino acids begins with the repositioning of their AASCs induced by immune/antibody pressure. We show that donor/acceptor atoms from any amino acid can determine cross-reactivity instead, provided they possess and present spatially pairing donor/acceptor atoms. By studying structural alignments for PDB deposited antibody-RBD 3D structures and relating them to published binding and neutralization profiles of the same antibodies, we demonstrate that minor structural alterations such as epitope AASC repositioning have a major impact on antibody effectiveness and, hence, should receive adequate attention given that protein structure dictates protein function.

Method to Find the Original Source of COVID-19 by Genome Sequence and Probability of Electron Capture

The purpose of this study was to find the original source of envelope protein (spiked surface) of the Covid-19. It was assumed that the envelope protein was related to ordinary proteins like the human liver enzymes as possible original sources. A comparison was made on the genome sequences of the envelope protein and the human liver enzymes. The results of computational experiments showed that the longest sequence, common in both groups, was as follows: glutamine acid (e) - glutamine acid (e) - threonine (t) - glycine (g). Upon this finding further investigation was performed on the molecular structure of this sequence;and the probabilities of electron captures by the protons of the atoms were computed to determine which atoms could connect the amino acids using the approximation method taken from the quantum mechanics. The study was continued to identify which amino acid grew the genome sequence of the envelope protein differently from the human liver enzymes. And it was found that the electron capture by the proton of the atom could explain the process that formed the genome sequence of the Covid-19’s envelope protein out from the human liver enzymes. To our opinion this method could be used for identification of other candidate proteins so that to find the original source of the virus. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Binding Energy Partition of Promising IRAK-4 Inhibitor (Zimlovisertib) for the Treatment of COVID-19 Pneumonia.

The technique of Fragment-Based Drug Design (FBDD) considers the interactions of different moieties of molecules with biological targets for the rational construction of potential drugs. One basic assumption of FBDD is that the different functional groups of a ligand interact with a biological target in an approximately additive, that is, independent manner. We investigated the interactions of different fragments of ligands and Interleukin-1 Receptor-Associated Kinase 4 (IRAK-4) throughout the FBDD design of Zimlovisertib, a promising anti-inflammatory, currently in trials to be used for the treatment of COVID-19 pneumonia. We utilised state-of-the-art methods of wave function analyses mainly the Interacting Quantum Atoms (IQA) energy partition for this purpose. By means of IQA, we assessed the suitability of every change to the ligand in the five stages of FBDD which led to Zimlovisertib on a quantitative basis. We determined the energetics of the interaction of different functional groups in the ligands with the IRAK-4 protein target and thereby demonstrated the adequacy (or lack thereof) of the changes made across the design of this drug. This analysis permits to verify whether a given alteration of a prospective drug leads to the intended tuning of non-covalent interactions with its protein objective. Overall, we expect that the methods exploited in this paper will prove valuable in the understanding and control of chemical modifications across FBDD processes.

A triatomic molecule is laser cooled and trapped

Miller discusses the study by John Doyle and colleagues at Harvard University on ultracold atoms and molecules. In March 2020, as the world was grappling with the implications of the COVID-19 pandemic, the team were faced with the bleak prospect of shutting down their experiments on ultracold atoms and molecules, perhaps indefinitely. So they turned their physics expertise to a rather different but more timely set of problems: Could N95 masks, in perilously short supply at the time, be decontaminated and reused?1 And how could the risks of airborne disease transmission be most effectively mitigated in a laboratory or office setting? Through their work, they helped Harvard develop a plan to safely and quickly reopen its research labs. They've now demonstrated the laser cooling and magneto-optical trapping of calcium monohydroxide, the first three-atom molecule to be so cooled and trapped.

A Review on Current Designation of Metallic Nanocomposite Hydrogel in Biomedical Applications

In the past few decades, nanotechnology has been receiving significant attention globally and is being continuously developed in various innovations for diverse applications, such as tissue engineering, biotechnology, biomedicine, textile, and food technology. Nanotechnological materials reportedly lack cell-interactive properties and are easily degraded into unfavourable products due to the presence of synthetic polymers in their structures. This is a major drawback of nanomaterials and is a cause of concern in the biomedicine field. Meanwhile, particulate systems, such as metallic nanoparticles (NPs), have captured the interest of the medical field due to their potential to inhibit the growth of microorganisms (bacteria, fungi, and viruses). Lately, researchers have shown a great interest in hydrogels in the biomedicine field due to their ability to retain and release drugs as well as to offer a moist environment. Hence, the development and innovation of hydrogel-incorporated metallic NPs from natural sources has become one of the alternative pathways for elevating the efficiency of therapeutic systems to make them highly effective and with fewer undesirable side effects. The objective of this review article is to provide insights into the latest fabricated metallic nanocomposite hydrogels and their current applications in the biomedicine field using nanotechnology and to discuss the limitations of this technology for future exploration. This article gives an overview of recent metallic nanocomposite hydrogels fabricated from bioresources, and it reviews their antimicrobial activities in facilitating the demands for their application in biomedicine. The work underlines the fabrication of various metallic nanocomposite hydrogels through the utilization of natural sources in the production of biomedical innovations, including wound healing treatment, drug delivery, scaffolds, etc. The potential of these nanocomposites in relation to their mechanical strength, antimicrobial activities, cytotoxicity, and optical properties has brought this technology into a new dimension in the biomedicine field. Finally, the limitations of metallic nanocomposite hydrogels in terms of their methods of synthesis, properties, and outlook for biomedical applications are further discussed.

Classical Thermodynamic Analysis of Deuterium-Based Fusion Reactions

The fusion reactions involving deuterium are of great interest for the exploitation of the fusion energy via magnetic-confinement devices. In classical thermodynamics, the spontaneity of a process is established through the assessment of the change in Gibbs free energy. So far, the feasibility of nuclear reactions has been characterized in terms of cross section and Q-value while the entropic term (T ΔS) has been neglected. Such an assumption is always justified for fission reactions where the term ΔS is positive. In the case of fusion reactions that operate at very high temperatures (106–107 K) and where ΔS is negative, the change in Gibbs free energy may be positive, making the reaction non-spontaneous. This paper proposes a classical thermodynamic analysis of D-based reactions of interest for the magnetic-confinement fusion applications. The entropy contribution was evaluated via the Sackur–Tetrode equation while the change in enthalpy was considered constant and as corresponding to the Q-value of the fusion reaction. The results of the thermodynamic analysis are compared with nuclear reaction feasibility criteria based on the reaction reactivity. The DT and D3He reactions show a high degree of spontaneity although the second one presents a lower reactivity. An increase in temperature could enhance the reactivity of the D3He reaction at the cost of decreasing its thermodynamic spontaneity. Both branches of the DD reaction are characterized by a much lower thermodynamic spontaneity than that of the DT and D3He reactions. Furthermore, at the temperature of their maximum cross section, the DD reactions exhibit a largely positive change in Gibbs free energy and, therefore, are not spontaneous. At the temperature of magnetic-confinement fusion machines (1.5 × 108 K), among the D-based reactions studied, the DT one exhibits the highest degrees of spontaneity and reactivity.

Evaluation and Study of Danao Flood Canal and BaiShou Bay Sediment in Huizhou under COVID -19 Epidemic

The COVID-19 epidemic has had a huge impact on human society, providing an opportunity for human beings to reflect on environmental governance. The sediment samples were collected from the Diversion Channel and Baishou Bay in Huizhou to analyze the element speciation distribution and pollution status. By graphite furnace atomic absorption spectrometry, atomic fluorescence spectrophotometry, flame atomic absorption Spectrophotometric methods to determine the content of the bottom sediments. The single factor index method, the Nemero comprehensive index method, the pollution load index method and the coefficient of variation analysis method were used to analyze. This study on the river bottom sediments of Huizhou is significant environmental effects of harmful elements. © 2021 Kriedt Enterprises Ltd. All right reserved.