Chemical Analysis Research Articles

MS2Lipid: A Lipid Subclass Prediction Program Using Machine Learning and Curated Tandem Mass Spectral Data

Background: Untargeted lipidomics using collision-induced dissociation-based tandem mass spectrometry (CID-MS/MS) is essential for biological and clinical applications. However, annotation confidence still relies on manual curation by analytical chemists, despite the development of various software tools for automatic spectral processing based on rule-based fragment annotations. Methods: In this study, we present a novel machine learning model, MS2Lipid, for the prediction of known lipid subclasses from MS/MS queries, providing an orthogonal approach to existing lipidomics software programs in determining the lipid subclass of ion features. We designed a new descriptor, MCH (mode of carbon and hydrogen), to increase the specificity of lipid subclass prediction in nominal mass resolution MS data. Results: The model, trained with 6760 and 6862 manually curated MS/MS spectra for the positive and negative ion modes, respectively, classified queries into one or several of 97 lipid subclasses, achieving an accuracy of 97.4% in the test set. The program was further validated using various datasets from different instruments and curators, with the average accuracy exceeding 87.2%. Using an integrated approach with molecular spectral networking, we demonstrated the utility of MS2Lipid by annotating microbiota-derived esterified bile acids, whose abundance was significantly increased in fecal samples of obese patients in a human cohort study. This suggests that the machine learning model provides an independent criterion for lipid subclass classification, enhancing the annotation of lipid metabolites within known lipid classes. Conclusions: MS2Lipid is a highly accurate machine learning model that enhances lipid subclass annotation from MS/MS data and provides an independent criterion.

Chemical analysis, antibacterial and anti-inflammatory effect of Achillea fragrantissima essential oil growing wild in Egypt

Abstract Background Achillea fragrantissima (F. Asteraceae) is traditionally used to treat skin infections and inflammation. The present work intended to prepare essential oils (EOs) from A. fragrantissima aerial parts growing widely in Egypt and investigate its antibacterial activity against skin-related pathogens and in vitro cell-based anti-inflammatory activity. Methods EOs of the fresh aerial parts were extracted by hydrodistillation (HD), microwave-assisted hydrodistillation (MAHD), and head-space (HS), while those of the dried ones were prepared by supercritical fluid (SF). The result EOs were analyzed using GC/MS. The antibacterial activity was evaluated alongside Pseudomonas aeruginosa ATCC 9027, Escherichia coli ATCC 8739, Staphylococcus aureus ATCC 25923, Streptococcus pyogenes ATCC 12344, Clostridium perfringens ATCC 13124 by agar diffusion, microwell dilution, and biofilm formation tests. The anti-inflammatory activity was evaluated by measuring tumor necrosis factor-alpha (TNF-α), interleukin 2 (IL-2), and 6 (IL-6) in lipopolysaccharides (LPS)- stimulated RAW 264.7 cells using ELISA assays in addition, expression of nitric oxide synthase (iNOS) was measured via western blot. Results The SF method gave the highest EO yield (1.50 mL v/w). Oxygenated components constituted the highest percentage in the four methods, 84.14, 79.21, 73.29 and 33.57% in the HS, HD, MAHD, and SF, respectively. Moreover, variation in the amount of identified compounds was apparent; in HS EO α-thujone (29.37%), artemisia ketone (19.59%), and santolina alcohol (14.66%) are major components, while α-thujone (20.38%) and piperatone (12.09%) were significant in HD. Moreover, ( +)-spathulenol (12.22%) and piperatone (10.48%) were significant in MAHD, while piperatone (14.83%) and β-sitosterol (11.07%) were significant in SF EO. HD, MAHD, and SF EOs exhibited susceptibility against P. aeruginosa (IZ = 9–14 mm), E. coli (11–13 mm), and C. perfringens (IZ = 10–14 mm) in agar diffusion assay. MAHD EOs demonstrated potent growth inhibition (MICs = 0.25–2 mg/mL), followed by HD EOs (MICs = 13–52 mg/mL) to all tested microorganisms in well microdilution assay. Also, they exert MBC values equal to or higher than the MICs. Furthermore, SF EOs inhibited the biofilm formation of all tested microorganisms by 65.12—80.84%. Specifically, MAHD and HD EOs efficiently suppress the biofilm of S. pyogenes (77.87%) and P. aeruginosa (60. 29%), respectively. Ultimately, HD and SF EOs showed anti-inflammatory activity by suppressing the TNF-α, IL-2, and IL-6 release and iNOS expression in LPS-stimulated RAW 264.7 macrophages. Conclusion A. fragrantissima EO is rich in oxygenated volatile compounds with antibacterial and anti-inflammatory activities. It is encouraged as a bioactive agent for adjusting skin infections, though additional studies are essential for their safety in clinical settings.

A Novel Machine Learning Model and a Web Portal for Predicting the Human Skin Sensitization Effects of Chemical Agents

Skin sensitization is a significant concern for chemical safety assessments. Traditional animal assays often fail to predict human responses accurately, and ethical constraints limit the collection of human data, necessitating a need for reliable in silico models of skin sensitization prediction. This study introduces HuSSPred, an in silico tool based on the Human Predictive Patch Test (HPPT). HuSSPred aims to enhance the reliability of predicting human skin sensitization effects for chemical agents to support their regulatory assessment. We have curated an extensive HPPT database and performed chemical space analysis and grouping. Binary and multiclass QSAR models were developed with Bayesian hyperparameter optimization. Model performance was evaluated via five-fold cross-validation. We performed model validation with reference data from the Defined Approaches for Skin Sensitization (DASS) app. HuSSPred models demonstrated strong predictive performance with CCR ranging from 55 to 88%, sensitivity between 48 and 89%, and specificity between 37 and 92%. The positive predictive value (PPV) ranged from 84 to 97%, versus negative predictive value (NPV) from 22 to 65%, and coverage was between 75 and 93%. Our models exhibited comparable or improved performance compared to existing tools, and the external validation showed the high accuracy and sensitivity of the developed models. HuSSPred provides a reliable, open-access, and ethical alternative to traditional testing for skin sensitization. Its high accuracy and reasonable coverage make it a valuable resource for regulatory assessments, aligning with the 3Rs principles. The publicly accessible HuSSPred web tool offers a user-friendly interface for predicting skin sensitization based on chemical structure.

Optical system characterization in Fourier ptychographic microscopy

Fourier ptychographic microscopy (FPM) is a recent technique to overcome the diffraction limit of a low numerical aperture (NA) objective lens by algorithmic post-processing of several low-resolution images. It can increase the space-bandwidth product of an optical system by computationally combining images captured under different illumination conditions. Vignetting determines the spatial extent of the bright and dark regions in the captured images. State-of-the-art analyses treat vignetting as a nuisance that needs to be reduced or excluded from algorithmic consideration using ad hoc decision rules. In contrast, this work investigates vignetting effects as a tool to infer a range of properties of the optical system. Generally, the goal of the FPM reconstruction algorithm is to achieve results that closely resemble the actual specimen at the highest resolution possible. However, as the optimization process does not necessarily guarantee a unique solution, we identify system properties that support alignment between computational predictions and empirical observations, potentially leading to a more accurate and reliable analysis. To achieve this, we characterize the individual system components of the experimental setup and compare experimental data to both, geometrical and wave optical simulations. We demonstrate that using vignetting as an analytical tool enables the modeling of the geometric and coherence properties of the optical system as evidenced by the good agreement between our simulation and experiment.

Mapping the evolution of liver aging research: A bibliometric analysis

BACKGROUND With the increasing of the global aging population, healthy aging and prevention of age-related diseases have become increasingly important. The liver, a vital organ involved in metabolism, detoxification, digestion, and immunity, holds a pivotal role in the aging process of organisms. Although extensive research on liver aging has been carried out, no bibliometric analysis has been conducted to evaluate the scientific progress in this area. AIM To analyze basic knowledge, development trends, and current research frontiers in the field via bibliometric methods. METHODS We conducted bibliometric analyses via a range of analytical tools including Python, the bibliometrix package in R, CiteSpace, and VOSviewer. We retrieved publication data on liver aging research from the Web of Science Core Collection Database. A scientific knowledge map was constructed to display the contributions from different authors, journals, countries, institutions, as well as patterns of co-occurrence keywords and co-cited references. Additionally, gene regulation pathways associated with liver aging were analyzed via the STRING database. RESULTS We identified 4288 articles on liver aging, authored by 24034 contributors from 4092 institutions across 85 countries. Notably, the years 1991 and 2020 presented significant bursts in publication output. The United States led in terms of publications (n = 1008, 25.1%), citations (n = 55205), and international collaborations (multiple country publications = 214). Keywords such as “lipid metabolism”, “fatty liver disease”, “inflammation”, “liver fibrosis” and “target” were prominent, highlighting the current research hotspots. Notably, the top 64 genes, each of which appeared in at least 8 articles, were involved in pathways essential for cell survival and aging, including the phosphatidylinositol 3-kinase/protein kinase B, Forkhead box O and p53 signaling pathways. CONCLUSION This study highlights key areas of liver aging and offers a comprehensive overview of research trends, as well as insights into potential value for collaborative pursuits and clinical implementations.

The AI-Powered Evolution of Big Data

The rapid advancement of artificial intelligence (AI), coupled with the global rollout of 4G and 5G networks, has fundamentally transformed the Big Data landscape, redefining data management and analysis methodologies. The ability to manage and analyze such vast and varied datasets has exceeded the capacity of any individual or organization. This study introduces an enhanced framework that expands upon the traditional four Vs of Big Data—volume, velocity, volatility, and veracity—by incorporating six additional dimensions: value, validity, visualization, variability, volatility, and vulnerability. This comprehensive framework offers a novel and straightforward approach to understanding and addressing the complexities of Big Data in the AI era. This article further explores the use of ‘Big D’, an AI-driven, RAG-based Big Data analytical bot powered by the ChatGPT-4o model (ChatGPT version 4.0). This article’s innovation represents a significant advance in the field, accelerating and deepening the extraction and analysis of insights from large-scale datasets. This will enable us to develop a more nuanced and comprehensive understanding of intricate data landscapes. In addition, we proposed a framework and analytical tools that contribute to the evolution of Big Data analytics, particularly in the context of AI-driven processes.

Simultaneous Removal of Strontium, Manganese, Lead and Arsenate from Wastewaters Using a Green and Low-Cost Adsorbent Derived from Nut Residues

The potential of a nut residue, activated only by physical means, to simultaneously adsorb Sr2+, Mn2+, Pb2+ and As5+ from contaminated waters was investigated. Mono-metal and multi-metal adsorption behavior and adsorption capacities by the solid material were compared for a range of initial metals concentrations, adsorbent dose, contact time and solution pH. The mechanisms of adsorption were examined by conducting structural, mineralogical and chemical analyses and applying two isotherm models to simulate experimental data. In the case of mono-metal adsorption, the maximum uptake of Sr2+ by the biochar was 12.3, of Mn2+ 23.8, of Pb2+ 24.7 and of As5+ 12.4 mg/g. In the case of multi-metal adsorption, the uptake of each metal was enhanced as the total ion flux density increased, revealing that there was no competition between these ions for biochar’s sorption sites. For an adsorbent dose of 2 g/L, the maximum adsorption capacity of biochar for Sr2+, Mn2+, Pb2+ and As5+ could be raised up to 47.6, 49.9, 25 and 48.7 mg/g, respectively. Potential adsorption mechanisms were chemical complexation or electron coordination between the metals and the biochar matrix, as well as mineral precipitation on the adsorbent surface.

Chemical analysis and concentrations of cannabidiol substances used for refractory epilepsy in Chilean patients. An underestimated worldwide risk.

The purpose of this study is to analyze composition of HMS (homemade CBD), NLS (non-licensed commercial products), and bioequivalent CBD (BES) collected from Chilean patients that voluntary accepted to analyze the "CBD-substance." Samples were collected through an open invitation for different patients to anonymously and free of charge participate in the analysis of CBD oil. The analysis of the active principle was performed using High-Resolution Liquid Chromatography (HPLC). A total of 35 samples were collected between March 2020 and September 2021, including two BES, six NLS, and 27 HMS products. The BES had an average CBD concentration of 89.15 mg/mL and an average THC concentration of 0.015 mg/mL, which complied with the maximum THC levels required by regulatory authorities (<0.2% THC.). The NLS (six samples) exhibited significant variability in CBD concentrations, ranging from a maximum of 78.5 mg/mL to a minimum of 0.1 mg/mL, with an average of 25.41 mg/mL. The THC concentrations ranged from 0 mg/mL to 2.43 mg/mL with an average of 0.62 mg/mL. The HMS products exhibited even higher variations of CBD concentrations, ranging from 0 to a maximum of 6.6 mg/mL. THC concentrations were even more variable, ranging from 0 mg/mL to 388 mg/mL. The medical community and patients involved should be aware that Hemp products are not pure and/or innocuous. HMS are likely to have high levels of THC and very low CBD, far away from therapeutic doses of CBD. CBD used in epilepsy should be restricted to licensed products, especially in children where THC toxicity is much more harmful. The study analyzed three types of CBD (cannabidiol) oils: homemade, non-licensed, and bioequivalent. Homemade and non-licensed products showed nonacceptable variance of CBD and THC concentration (tetrahydrocannabinol), in some cases with 0 mgs of CBD and many beyond THC maximum accepted. The THC is another component found in cannabis and is responsible for the neurotoxic effects. Only bioequivalent products showed concentrations of CBD and THC acceptable for epilepsy treatment, therefore are the only products recommended for such purpose.

Design and FPGA Implementation of a Hyper-Chaotic System for Real-time Secure Image Transmission

Recently, chaos theory has been widely used in multimedia and digital communications due to its unique properties that can enhance security, data compression, and signal processing. It plays a significant role in securing digital images and protecting sensitive visual information from unauthorized access, tampering, and interception. In this regard, chaotic signals are used in image encryption to empower the security; that's because chaotic systems are characterized by their sensitivity to initial conditions, and their unpredictable and seemingly random behavior. In particular, hyper-chaotic systems involve multiple chaotic systems interacting with each other. These systems can introduce more randomness and complexity, leading to stronger encryption techniques. In this paper, Hyper-chaotic Lorenz system is considered to design robust image encryption/ decryption system based on master-slave synchronization. Firstly, the rich dynamic characteristics of this system is studied using analytical and numerical nonlinear analysis tools. Next, the image secure system has been implemented through Field-Programmable Gate Arrays (FPGAs) Zedboard Zynq xc7z020-1clg484 to verify the image encryption/decryption directly on programmable hardware Kit. Numerical simulations, hardware implementation, and cryptanalysis tools are conducted to validate the effectiveness and robustness of the proposed system.

Laser ablation inductively coupled plasma mass spectrometry measurements for high-resolution chemical ice core analyses with a first application to an ice core from Skytrain Ice Rise (Antarctica)

Abstract. Conventional methods of inorganic impurity analysis do not provide high enough depth resolution for many scientific questions in ice core science. In this study, we present a setup of laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) for high-resolution glacier ice impurity analysis to the sub-millimetre scale. This setup enables ice core chemical impurity analysis to a depth resolution of ∼182 µm while consuming only very small amounts of ice. The system performs simultaneous analysis of sodium, magnesium and aluminium incorporated in the ice matrix. In this case study within the framework of the WACSWAIN (WArm Climate Stability of the West Antarctic Ice Sheet in the last INterglacial) project, our method is applied to a selection of samples from the Skytrain ice core (West Antarctica) over a total length of 6.7 m consisting of about 130 single samples. The main goal of this study is to use the new LA-ICP-MS method to extract meaningful climate signals on a depth resolution level beyond the limits of continuous-flow analysis (CFA). A comparison between low-resolution CFA data and the high-resolution LA-ICP-MS data reveals generally good agreement on the decimetre scale. Stacking of parallel laser measurements together with frequency analysis is used to analyse the high-resolution LA-ICP-MS data at millimetre resolution. Spectral analysis reveals that despite effects of impurity accumulation along ice crystal grain boundaries, periodic concentration changes in the Skytrain ice core on the millimetre scale can be identified in ice from 26.8 ka (kiloyears before present, i.e. 1950 CE). These findings open new possibilities for climate data interpretation with respect to fast changes in the last glacial period and beyond, for example within the Beyond EPICA oldest-ice project.

Chemical genetics analysis suggests the involvement of Aurora kinase and MAPKs in aluminum-induced malate secretion in Arabidopsis.

Chemical genetics is a multidisciplinary research method. In this study, it is used to screen compounds that promote aluminum-induced malate secretion in Arabidopsis thaliana. Inhibition of p38 mitogen-activated protein kinase (p38 MAPK; LY2228820) significantly increased the transcription of Arabidopsis thaliana aluminum-activated malate transporter 1 (AtALMT1) and sensitive to proton rhizotoxicity 1 (STOP1)-regulated genes, multidrug and toxic compound extrusion and aluminum sensitive 3, but not AtSTOP1 and the Al-biomarker genes At3g28510, At5g13320, suggesting that LY2228820 increased the early expression of STOP1-regulated genes without affecting AtSTOP1 expression. Inhibition of p38 MAPK (LY2228820) and Aurora A (MLN8237) increased aluminum-activated malate transport via AtALMT1, suggesting that both MLN8237 and LY2228820 interfere with AtALMT1 activity. An increase in root elongation was also observed in Arabidopsis after applying compounds LY2228820 and MLN8237. Thus, both LY2228820 and MLN8237 may play important roles in alleviating the inhibitory effects of aluminum on roots.

Comprehensive Assessment of Carbon Disulfide Exposure in Laboratories—Air and Biological Monitoring Approaches

Carbon disulfide (CS2) is a highly toxic and flammable solvent extensively used in chemical processes and laboratory analyses. This review examines both air and biological monitoring methods for assessing the exposure of laboratory workers to CS2. Emphasis is placed on the measurement of airborne CS2 concentrations and the monitoring of 2-thiothiazolidine-4-carboxylic acid (TTCA) in urine, a key biomarker of exposure. By analysing case studies and practical applications, the paper outlines the effectiveness and limitations of current monitoring techniques. Additionally, the review addresses key challenges such as CS2 volatility, dietary influence on biomarker levels, and the sufficiency of protective measures, including nitrile gloves. It also proposes best practices to mitigate exposure, such as improved ventilation, the use of polyvinyl alcohol gloves, and the substitution of CS2 with less hazardous solvents. This comprehensive review underscores the need for continuous vigilance in managing chemical exposure and offers insights into how laboratories can better protect their workers by integrating air and biological monitoring strategies.

Comparative Study on the Proximate Composition and Amino Acid Levels in Chanterelle (Cantharellus cibarius) and Wood Ear (Auricularia auricula) Mushroom Samples

Mushrooms have been consumed by mankind for millennia. They are macrofungi with a distinctive fruiting body which can be hypogeous or epigeous, large enough to be seen with unaided eyes. They are not widely consumed due to lack of information on its nutritive value. Therefore, this research was carried out to compare the proximate gross energy composition as well as amino acids levels in two selected edible mushrooms (Cantharellus cibarius and Auricularia auricula). Fully matured species of Chanterelle mushroom (Cantherellus cibarius) and Wood ear mushroom (Auricularia auricula) were collected from different parts of Southern and Northern Cross River; Ikom and Bekwara precisely. The collected samples were air dried for 5 days and then stored in transparent polythene bag for analysis. The dried and stored mushroom were pounded to powdered form and then subjected to amino acid analysis using isocratic HPLC and proximate analysis for proximate composition using the standard methods of Association of Official Analytical Chemist (AOAC). The results of this research showed that chanterelle mushroom has high concentration of amino acids compared to Wood ear mushroom. However, there was significant differences (p&lt;0.05) in the levels of isoleucine in both mushrooms. There were no significant differences in the proximate composition and gross energy levels of both mushroom species. Some of the amino acids detected in both mushrooms were: methionine, threonine, isoleucine, leucine, phenylalanine, valine, tryptophan, histidine, arginine, aspartic acid, glycine, alanine and glutamic acid. Based on the findings of this study, the two edible mushrooms were observed to have appreciable levels of gross energy and amino acids. However, Chanterelle mushroom had higher protein composition than wood ear. Hence, it can be concluded that Chanterelle mushroom has greater nutritive value and more suitable for consumption.

Eliminating Scraps in Refrigerator Door Sealing—A Six Sigma Case Study

This paper applies the Six Sigma method to an investigation and analysis of the factors contributing to sealing problems encountered in a refrigerated appliance model. By adopting a rigorous and systematic approach, the Six Sigma method relies on the use of advanced statistical and analytical tools to minimize variability and optimize processes. By utilizing the Six Sigma methodology, this work not only identifies and remedies sealing-related problems, but also contributes to a robust and efficient manufacturing process. The proposed methodology adopts the DMAIC approach and its associated tools to evaluate the impact of waste on the production process. This study aims to demonstrate how the DMAIC approach can effectively assist the company in minimizing scrap. Furthermore, detailed recommendations regarding the application and implementation of DMAIC tools are provided, enabling the company to thoroughly assess its existing processes. These insights will empower the company to identify areas for improvement and implement strategies for ongoing enhancement and operational excellence.

Integrated Chemical and Ecotoxicological Assessment of Metal Contamination in the Andong Watershed: Identifying Key Toxicants and Ecological Risks

This study employed an integrated field monitoring approach, combining chemical analysis and ecotoxicity testing of multiple environmental matrices—water, sediment, and sediment elutriates—to comprehensively assess the environmental health of the Andong watershed, located near a Zn smelter and mining area. The primary objectives were to evaluate the extent of metal contamination, identify key toxicants contributing to ecological degradation, and trace the sources of these pollutants. Our findings revealed severe metal contamination and significant ecotoxicological effects both in proximity to and downstream from industrial sites. Specifically, Cd, Zn, and Pb were strongly linked to the smelter, while Hg, Ni, Cu, and As were predominantly associated with mining activities in the tributaries. To further assess toxicity of field-collected sediment and their elutriates, a logistic regression analysis was employed to estimate benchmark values for distinguishing between toxic and non-toxic samples, using the sum of toxic units for sediment elutriates and the mean probable effect level (PEL) quotient for sediment toxicity. These models demonstrated greater predictive accuracy than conventional benchmarks for determining toxicity thresholds. Our results highlight that integrating chemical and ecotoxicological monitoring with site-specific concentration–response relationships enhances the precision of ecological risk assessments, facilitating more accurate identification of key toxicants driving mixture toxicity in complex, pollution-impacted aquatic ecosystems.

Engineering Epitaxial Interfaces for Topological Insulator — Superconductor Hybrid Devices with Al Electrodes

AbstractProximity‐induced superconductivity in hybrid devices of topological insulators and superconductors offers a promising platform for the pursuit of elusive topological superconductivity and its anticipated applications, such as fault‐tolerant quantum computing. To study and harness such hybrid devices, a key challenge is the realization of highly functional material interfaces with a suitable superconductor featuring 2‐periodic parity‐conserving transport to ensure a superconducting hard‐gap free of unpaired electrons, which is important for Majorana physics. A superconductor well‐known for this characteristic is Al, however, its direct integration into devices based on tetradymite topological insulators has so far been found to yield non‐transparent interfaces. By focusing on Bi2Te3‐Al heterostructures, this study identifies detrimental interdiffusion processes at the interface through atomically resolved structural and chemical analysis, and showcases their mitigation by leveraging different interlayers – namely Nb, Ti, Pd, and Pt – between Bi2Te3 and Al. Through structural transformation of the interlayer materials (X) into their respective tellurides (XTe2) atomically‐sharp epitaxial interfaces are engineered and further characterized in low‐temperature transport experiments on Al‐X‐Bi2Te3‐X‐Al Josephson junctions and in complementary density functional theory calculations. By demonstrating functional interfaces between Bi2Te3 and Al, this work provides key insights and paves the way for the next generation of sophisticated topological devices.

Magnetic Anisotropic Effects in Charged Aza[10]annulene Analogs with a Non-planar Carbon Framework.

Classically, aromaticity portrays the unique stability and peculiar reactivities of cyclic planar conjugated systems with (4n+2) π electrons. Understanding the electronic environments in new chemical frameworks through experimental and theoretical validation is central to this ever-expanding theme in chemical science. Such investigations in curved π-surfaces have special significance as they can unravel the variations when the planarity requirement is slightly lifted. In this report, we discuss the synthesis,spectroscopicand theoretical studies involving a new group of cyclazine analogs having a charged aza[10]annulene periphery, centrally locked through a sp3 carbon. Magnetic anisotropic effects arising from electron delocalization through its curved π-surface were mapped through a specific set of chemical groups introduced through this sp3 carbon. The nucleus-independent chemical shift calculations revealed negative chemical shift values, indicating the aromatic nature of the aza[10] annulene rim. This is corroborated by a clockwise diatropic ring current, evident from anisotropy-induced current density analysis. Variations in the chemical shift of NMR signals in these systems were also computationally examined through isotropic chemical shielding surface analysis.

Interview with Professor Colin Murrell

Prof. Colin Murrell, a distinguished microbiologist and Emeritus Professor at the University of East Anglia, UK, is well known for his contributions to various areas of environmental microbiology and microbial ecology. Prof. Murrell has received several awards, including election to membership of the European Molecular Biology Organisation, the European Academy of Microbiology, the Chinese Academy of Sciences Distinguished Professor (Einstein) Award. He was awarded a highly prestigious European Research Council Advanced Grant and has been member of many editorial boards of leading microbiological journals including Environmental Microbiology and the ISME Journal. He has graduated over 60 PhD students and supervised around 150 researchers throughout his career. His research interests are immense, extending from the development of analytical tools in molecular microbial ecology to their testing in the field, which is reflected in his extensive publication list of over 350 highly cited papers in prestigious journals. His pioneering research has significantly improved our understanding of microbial processes in diverse environments, from soil to aquatic and marine ecosystems. More recently, he has extended his scientific curiosity to karst and caves, in particular to the Movile Cave in Romania, which represents a cornerstone for understanding the role of chemolithoautotrophy in caves.

Anthropogenic Impact on Soils of Cities Irkutsk, Angarsk

The morphological field description of soil profiles of the territory of Irkutsk region was carried out. Samples of soils, soil-forming rocks and vegetation were taken for further physical and chemical analyses to determine soil properties in the studied areas. Sample preparation of soils was carried out, phytotoxicity of soils was analyzed. Processing of the obtained data was carried out, as a result of which the percentage of germination of radish seeds in the upper horizons of soils of the key areas of Irkutsk and Angarsk cities was revealed, the length of shoots and the length of roots in the soils of the studied samples were measured, the index of soil toxicity was calculated.

Heat treatment effect on the carbides in T-15 and M-4 steels

ABSTRACT In the present work, the effect of heat treatment on the microstructure and mechanical properties of T-15 and M-4 high-speed steels was investigated. These steels were produced by powder metallurgy. Due to their frictional wear resistance properties, T-15 and M-4 high-speed steels are widely used in the cutting tool manufacture of the metalworking industry. A heat treatment was applied to both steels, heating them to 1250°C, then air quenching and, finally tempering at 550°C for 2 h, 3 times (triple tempering at 550°C). Steels were characterized by hardness test, metallographic analysis, tensile strength test, and fracture analysis after the heat treatment. Results were compared and related to the metallurgical microstructure, mainly to the distribution of carbides, and also to fracture type and characteristics. Test results and chemical analysis showed important differences between T-15 and M-4 steels.