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Review Papers in Analytical Chemistry
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Review Papers in Analytical Chemistry

A special issue of Molecules (ISSN 1420-3049). This special issue belongs to the section "Analytical Chemistry".

Deadline for manuscript submissions: 31 August 2024 | Viewed by 5435

Special Issue Editor

Dr. Giorgio S. Senesi

E-Mail Website
Guest Editor
CNR, Istituto per la Scienza e Tecnologia dei Plasmi (ISTP), Sede di Bari, 70126 Bari, Italy
Interests: laser-induced breakdown spectroscopy applied to minerals, gems, rocks, meteorites, soils, fertilizers, plants and cultural heritage; laser–matter interaction; laser spectroscopy; morphological characterization techniques (AFM, SEM, TEM); nanocrystalline diamond films
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In this Special Issue, “Review Papers in Analytical Chemistry”, Molecules intends to publish high-quality review papers and critical overviews addressing the elucidation of fundamental and/or applicative aspects and new developments of cutting-edge analytical chemistry research, aiming to help analytical chemists and other users of analytical techniques.

The subjects can encompass all branches of modern analytical chemistry such as spectroscopy, chromatography, mass spectrometry, electrochemistry and trace analysis, and their applications in areas such as analytical instrumentation, environmental analysis and monitoring, biomedical analysis, biomolecular analysis, biosensors, chemical analysis, chemometrics, clinical chemistry, drug discovery, the pharmaceutical industry, food analysis, forensic science, laboratory automation, materials science, metabolomics, pesticide residue analysis, surface science, water analysis and monitoring automation and other relevant areas. Review articles should bring the expert up to date in a concise manner and provide researchers with an overview of new techniques and methods.

Distinguished researchers from all over the world are invited to contribute to this issue. In order to avoid overlapping topics, potential contributors/invited authors are kindly requested to submit a tentative article title and a one- or two-page description/table of contents the editors for pre-evaluation.

Topics

  • Analytical chemistry
  • Analytical spectroscopy and optical detection methods
  • Analytical electrochemistry
  • Analytical biochemistry
  • Separation sciences and their analytical applications
  • Mass spectrometry
  • Chemical sensors
  • Trace analysis and particulate matter analysis
  • Surface analysis and chemical imaging
  • Chemometry

Dr. Giorgio S. Senesi
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Molecules is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • analytical chemistry
  • analytical spectroscopy
  • medical science
  • forensic science
  • cultural heritage
  • food analysis

Published Papers (3 papers)

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Review

41 pages, 5168 KiB  
Review
Illuminating the Tiny World: A Navigation Guide for Proper Raman Studies on Microorganisms
by Sandra Baaba Frempong, Markus Salbreiter, Sara Mostafapour, Aikaterini Pistiki, Thomas W. Bocklitz, Petra Rösch and Jürgen Popp
Molecules 2024, 29(5), 1077; https://doi.org/10.3390/molecules29051077 - 29 Feb 2024
Viewed by 1422
Abstract
Raman spectroscopy is an emerging method for the identification of bacteria. Nevertheless, a lot of different parameters need to be considered to establish a reliable database capable of identifying real-world samples such as medical or environmental probes. In this review, the establishment of [...] Read more.
Raman spectroscopy is an emerging method for the identification of bacteria. Nevertheless, a lot of different parameters need to be considered to establish a reliable database capable of identifying real-world samples such as medical or environmental probes. In this review, the establishment of such reliable databases with the proper design in microbiological Raman studies is demonstrated, shining a light into all the parts that require attention. Aspects such as the strain selection, sample preparation and isolation requirements, the phenotypic influence, measurement strategies, as well as the statistical approaches for discrimination of bacteria, are presented. Furthermore, the influence of these aspects on spectra quality, result accuracy, and read-out are discussed. The aim of this review is to serve as a guide for the design of microbiological Raman studies that can support the establishment of this method in different fields. Full article
(This article belongs to the Special Issue Review Papers in Analytical Chemistry)
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23 pages, 2381 KiB  
Review
Polyamine-Derived Aminoaldehydes and Acrolein: Cytotoxicity, Reactivity and Analysis of the Induced Protein Modifications
by Marek Šebela and Michaela Rašková
Molecules 2023, 28(21), 7429; https://doi.org/10.3390/molecules28217429 - 04 Nov 2023
Viewed by 1179
Abstract
Polyamines participate in the processes of cell growth and development. The degradation branch of their metabolism involves amine oxidases. The oxidation of spermine, spermidine and putrescine releases hydrogen peroxide and the corresponding aminoaldehyde. Polyamine-derived aminoaldehydes have been found to be cytotoxic, and they [...] Read more.
Polyamines participate in the processes of cell growth and development. The degradation branch of their metabolism involves amine oxidases. The oxidation of spermine, spermidine and putrescine releases hydrogen peroxide and the corresponding aminoaldehyde. Polyamine-derived aminoaldehydes have been found to be cytotoxic, and they represent the subject of this review. 3-aminopropanal disrupts the lysosomal membrane and triggers apoptosis or necrosis in the damaged cells. It is implicated in the pathogenesis of cerebral ischemia. Furthermore, 3-aminopropanal yields acrolein through the elimination of ammonia. This reactive aldehyde is also generated by the decomposition of aminoaldehydes produced in the reaction of serum amine oxidase with spermidine or spermine. In addition, acrolein is a common environmental pollutant. It causes covalent modifications of proteins, including carbonylation, the production of Michael-type adducts and cross-linking, and it has been associated with inflammation-related diseases. APAL and acrolein are detoxified by aldehyde dehydrogenases and other mechanisms. High-performance liquid chromatography, immunochemistry and mass spectrometry have been largely used to analyze the presence of polyamine-derived aminoaldehydes and protein modifications elicited by their effect. However, the main and still open challenge is to find clues for discovering clear linkages between aldehyde-induced modifications of specific proteins and the development of various diseases. Full article
(This article belongs to the Special Issue Review Papers in Analytical Chemistry)
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21 pages, 2531 KiB  
Review
Exploring the Steps of Infrared (IR) Spectral Analysis: Pre-Processing, (Classical) Data Modelling, and Deep Learning
by Azadeh Mokari, Shuxia Guo and Thomas Bocklitz
Molecules 2023, 28(19), 6886; https://doi.org/10.3390/molecules28196886 - 30 Sep 2023
Cited by 2 | Viewed by 2456
Abstract
Infrared (IR) spectroscopy has greatly improved the ability to study biomedical samples because IR spectroscopy measures how molecules interact with infrared light, providing a measurement of the vibrational states of the molecules. Therefore, the resulting IR spectrum provides a unique vibrational fingerprint of [...] Read more.
Infrared (IR) spectroscopy has greatly improved the ability to study biomedical samples because IR spectroscopy measures how molecules interact with infrared light, providing a measurement of the vibrational states of the molecules. Therefore, the resulting IR spectrum provides a unique vibrational fingerprint of the sample. This characteristic makes IR spectroscopy an invaluable and versatile technology for detecting a wide variety of chemicals and is widely used in biological, chemical, and medical scenarios. These include, but are not limited to, micro-organism identification, clinical diagnosis, and explosive detection. However, IR spectroscopy is susceptible to various interfering factors such as scattering, reflection, and interference, which manifest themselves as baseline, band distortion, and intensity changes in the measured IR spectra. Combined with the absorption information of the molecules of interest, these interferences prevent direct data interpretation based on the Beer–Lambert law. Instead, more advanced data analysis approaches, particularly artificial intelligence (AI)-based algorithms, are required to remove the interfering contributions and, more importantly, to translate the spectral signals into high-level biological/chemical information. This leads to the tasks of spectral pre-processing and data modeling, the main topics of this review. In particular, we will discuss recent developments in both tasks from the perspectives of classical machine learning and deep learning. Full article
(This article belongs to the Special Issue Review Papers in Analytical Chemistry)
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