Chemical Analysis Research Articles

Abstract PR017: Anti-metastatic immunotherapy discovery using ex vivo lung tissue cultures and high-throughput single-cell chemical transcriptomics

Abstract Introduction: Tumors systemically remodel the immune system during metastasis. Developing anti-metastatic immunotherapies that target these tumor-immune interactions to make the metastatic niche hostile colonization would represent a paradigm shift in cancer treatment. However, traditional high-throughput screening (HTS) platforms that use simple read-outs and contrived in vitro systems are ill-suited to identify such therapies. In contrast, HTS platforms that accurately model the metastatic niche and use high-dimensional read-outs such as multiplexed single-cell RNA-sequencing (scRNA-seq) can accurately profile nuanced perturbation responses in individual immune cell types and therefore have the potential to discover anti-metastatic immunotherapies. In this study, we describe the development of an ex vivo lung tissue culture HTS platform that preserves immune gene expression signatures observed in the in vivo metastatic niche and is amenable to single-cell chemical transcriptomic analysis using MULTI- seq (McGinnis et al., Nature Methods, 2019). Inspired by our recent description of myeloid cell TLR-NFκB inflammation during breast cancer lung metastasis (McGinnis et al., Cancer Cell, 2024), we then performed the first anti-metastatic immunotherapy drug screen and identified TLR-NFκB inhibitors that effectively operate on all desired myeloid cell types in the lung metastatic niche. Methods and Results: Building upon existing techniques for culturing precision-cut lung slices (Wu et al., Journal of Experimental Medicine, 2024) and patient- derived tumor fragments (Voabil et al., Nature Medicine, 2021), we established and optimized an ex vivo lung tissue culture system that enables 48-hour culturing of lung slices isolated from 4T1 tumor-bearing mice. scRNA-seq profiling revealed successful capture of all relevant immune cell types and retention of metastasis-associated gene expression programs (e.g., myeloid TLR-NFκB inflammation and neutrophil degranulation) following culture. We then scaled our platform to address how myeloid cells in the lung metastatic niche respond to perturbations targeting every component of the canonical TLR-NFκB signaling cascade. Cell-type-specific perturbation modeling and quantification of TLR-NFκB signaling inhibition identified compounds that optimally perturb all intended myeloid cell types (e.g., tissue-resident macrophages, neutrophils, and monocytes) and represent prioritized candidates for future in vivo validation studies to assess impact on metastatic disease progression. Conclusions: In this study, we describe the development and application of a novel HTS platform that couples ex vivo lung tissue cultures with single-cell chemical transcriptomics to identify anti-metastatic immunotherapy candidates. We demonstrate how our platform can identify TLR-NFκB signaling inhibitors that optimally operate in the lung metastatic niche, paving the way for future interrogation of additional metastasis-associated immune cell signaling pathways in different disease and tissue backgrounds. Citation Format: Chris McGinnis, Winnie Yao, Ansuman Satpathy. Anti-metastatic immunotherapy discovery using ex vivo lung tissue cultures and high-throughput single-cell chemical transcriptomics [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor-body Interactions: The Roles of Micro- and Macroenvironment in Cancer; 2024 Nov 17-20; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(22_Suppl):Abstract nr PR017.

Drinking water is the urolithiasis development factor among the rural population of a single region

BACKGROUND: The urolithiasis incidence in the Nizhny Novgorod Region exceeds the national average that determines the importance of analyzing the causes of its development and creating preventive measures. AIM: To evaluate the relationship between the urolithiasis incidence and drinking water composition consumed by the rural population of the Nizhny Novgorod Region. MATERIALS AND METHODS: A chemical analysis of drinking water was performed in 50 rural districts of the Nizhny Novgorod Region (a total of 61 samples). Water was taken from centralized water supply sources, artesian wells and boreholes, and springs. The relationship between the urolithiasis incidence and chemical composition measures of drinking water was assessed. RESULTS: Differences in the impurity content of drinking water were found between districts with different values of urolithiasis incidence. Exceeding the standard values for impurities specified in the Sanitary regulations and standards (SanPin) was most commonly detected in water from districts with the highest incidence of urolithiasis. An increase in the calcium/magnesium ratio was the most commonly noted in drinking water from these districts. In 41 (67.2%) of 61 samples, an increase of calcium level was detected. The hardness of drinking water was higher than the standard in 33.3–38.8% of samples depending on the water intake source. CONCLUSIONS: Drinking water with a high level of hardness and mineralization is one of the etiological factors for the development of urolithiasis in Nizhny Novgorod Region. In rural areas of this region with a high incidence of urolithiasis, the monitoring of the state of central water supply sources and the impurity content in drinking water should be intensified.

Leveraging infrared spectroscopy for automated structure elucidation.

The application of machine learning models in chemistry has made remarkable strides in recent years. While analytical chemistry has received considerable interest from machine learning practitioners, its adoption into everyday use remains limited. Among the available analytical methods, Infrared (IR) spectroscopy stands out in terms of affordability, simplicity, and accessibility. However, its use has been limited to the identification of a selected few functional groups, as most peaks lie beyond human interpretation. We present a transformer model that enables chemists to leverage the complete information contained within an IR spectrum to directly predict the molecular structure. To cover a large chemical space, we pretrain the model using 634,585 simulated IR spectra and fine-tune it on 3,453 experimental spectra. Our approach achieves a top-1 accuracy of 44.4% and top-10 accuracy of 69.8% on compounds containing 6 to 13 heavy atoms. When solely predicting scaffolds, the model accurately predicts the top-1 scaffold in 84.5% and among the top-10 in 93.0% of cases.

Potential biological applications of environment friendly synthesized iron oxide nanoparticles using Sageretia thea root extract.

The green synthesis of Iron oxide nanoparticles (IONPs) has shown numerous advantages over conventional physical and chemical synthesis methods as these methods non-ecofriendly and uses toxic chemicals and complicated equipments. In present study, Iron oxide nanoparticles (IONPs) were created using simple, sustainable, eco-friendly and green chemistry protocol. The roots of novel medicinal plant Sageretia thea was used as a bio-template for the preparation of IONPs. Further, the synthesis of IONPs was confirmed using different analytical tools like UV-Vis, FT-IR, XRD, EDX, and SEM. The average sizes of (NPs) were found to be 16.04nm. Further, asynthesized IONPs were evaluated for several biological potentials including antibacterial, antifungal Anti-radical potentials (DPPH) and cytotoxicity assays. Antibacterial potencies were investigated using bacterial strains (in the concentration range of 1000-31.25µg/mL) revealing significant antibacterial potentials. ABA and SAU was reported to be least susceptible while KPN was observed to be most susceptible strain in bactericidal studies. Further, different fungal strains were used to investigate the antifungal potentials of IONPs (in the concentration range of 1000-31.25µg/mL) and revealed strong antifungal potencies against different pathogenic strains. Furthermore, MRA, FA and ANI were most susceptible and ABA was least susceptible in fungicidal examination. Significant cytotoxicity potential was examined using brine shrimps cytotoxicity assay, thus revealing the cytotoxic potential of asynthesized IONPs. The IC50 for S. thea based IONPs was recorded as 33.85µg/mL. Strong anti-radical potentials (DPPH) assay was performed to evaluate the ROS scavenging potential of S.T@IONPs. The highest scavenging potential was noted as 78.06%, TRP as 81.92% and TAC as 84% on maximum concentration of 200µg/mL. In summary, our experimental results concluded, that asynthesized IONPs have strong antibacterial, antifungal, DPPH scavenging and cytotoxic potentials and can be used in different biological applications. In nutshell, our as-prepared nanoparticles have shown potential bioactivities and we recommend, different other in vitro and in vivo biological and bioactivities to further analyze the biological potentials.

Analysis of Mineral Composition and Isotope Ratio as Part of Chemical Profiles of Apples for Their Authentication

One of the consequences of the globalisation of food markets is the effort enabling the control of food security and its origin. This might be traced by using different chemical composition analyses. However, for Central Europe, there is a lack of knowledge about the original reference values as well as their heterogeneity among the lands and countries. This study focused on characterizing the mineral profiles of apple tree fruits and comparing these profiles among different districts in Central Europe. The fruits of the apple cultivars ‘Gala’ and ‘Golden Delicious’ originated in the Czech Republic and Poland. The mineral and isotopic content of the apple fruit flesh was analysed using ICP-MS. The data were processed using the ANOVA test and compositely analysed using the PCA and LDA models. The results show relatively high variation in element distribution, particularly 87Sr/86Sr, Mn, Zn, Cu, Ca, P, and B, ranging between 20.6 and67.9% for both cultivars on average. However, their high variability within particular districts complicates the resolution of the LDA model. The reasons are linked to the geomorphological and pedological heterogeneity of the analysed districts as well as the particular sensitivity of the set of chosen primers to agronomic practices and tree performance. For this region, only partial separation among districts could be obtained by P, Ca, and Cu content, as well as the isotopic ratio of 10B/11B. However, the resolution of the geographical discrimination needs to be improved by an enhanced set of primers, the use of more precise analytical techniques for the Sr isotopic ratio, or by multiple chemical analyses. Furthermore, the heterogeneity of the analysed districts could be tackled by more detailed analyses at the level of micro-regions.

Comparative Analysis of Tetravalent Actinide Schiff Base Complexes: Influence of Donor and Ligand Backbone on Molecular Geometry and Metal Binding.

A series of isostructural early actinide AnIV complexes was synthesized in order to investigate the influence of a conjugated framework in the ligand backbone on An bonding. Therefore, the AnIV complexes [An(pyrophen)2] (An = Th, U, Np, and Pu) with the pure N-donor ligand bis(2-pyrrolecarbonylaldehyde)-o-phenylenediamine referred to as pyrophen, were synthesized and characterized. Solid state analysis via single-crystal X-ray diffraction (SC-XRD) reveals two sets of ligands binding in an almost orthogonal arrangement to the actinide center. For the larger actinides Th and U, the coordination sphere allows for additional coordination by a solvent molecule. Nuclear magnetic resonance spectroscopy (NMR) studies show the presence of highly symmetrical complexes in solution in good agreement with the solvent-free solid structures. While SC-XRD suggests mainly ionic binding, an analysis of paramagnetic NMR contributions and quantum chemical bond analysis hint towards significant covalency in the U, Np, and Pu compounds. This series of An complexes allowed for a thorough structural and theoretical comparison of a conjugated system to a closely related N-donor ligand (pyren)[1] as well as to the mixed N,O Schiff base ligands salophen (conjugated) and salen (non-conjugated).

Chemical analysis of toxic elements: total cadmium, lead, mercury, arsenic and inorganic arsenic in local and imported rice consumed in the Kingdom of Saudi Arabia.

Rice consumption is a pathway for human exposure to toxic elements. Although rice is a major staple in the Kingdom of Saudi Arabia (KSA) there is limited published data about its toxic element composition. Both imported and locally grown Hassawi rice in Saudi Arabia were collected, digested then analysed by HPLC-ICP-MS for inorganic arsenic (i-As) and byICP-MS for As, Cd, Pb and Hg. Of these toxic elements, i-As was present at concentrations that might give rise to material concerns about human exposure and public health. Hassawi rice (mean 43 ± 5µg/kg) was found to have significantly lower concentrations of i-As than imported rice (mean 73 ± 8µg/kg). The estimated exposure of adults consuming imported rice in one KSA city reached 0.3µg/kg-bw/day, within the margin of safety of the recently withdrawn WHO PTWI for i-As of 2.1µg/kg-bw/day and higher than EFSA's 0.06µg/kg-bw/day skin cancer BMDL05.

Nutrients and Antioxidant Composition of Local Condiment “Ogiri” Produced from Different Leguminous Seeds

‘Ogiri’ refers to a fermented oily paste that is used as soup condiments for its strong smell. Apart from the fact that it’s mostly used in soup preparation because of the strong pungent odour and organoleptic properties, it also impact nutrients to soup. This study investigated the nutrients and antioxidant composition of Ogiri produced from different leguminous seeds. Raw material such as melon (EGU) and sesame (SES) seeds were procured from Oja Oba (Oba Market) in Owo, Ondo State while pumpkin (PUM) and Castor (CAS) seed were purchased at Upper Iweka market, Onitsha Anambra State, Nigeria. The raw materials were processed into ‘Ogiri’ using traditional methods and were subjected to chemical analysis using standard analytical methods.” Data generated were subjected to One-way Analysis of Variance (ANOVA) and means were separated using Duncan Multiple Range Test at 5% level of significance. Findings shows that the moisture content was significantly (P<0.05) higher in PUM than any other sample. Sample SES was significantly (P<0.05) higher in Ash (10.22g /100g) content, and fibre (11.21g/100g) while EGU was significantly (P<0.05) higher in fat (30.17g/100g) and protein (29.30g/100g). CAS had the highest carbohydrate content (27.58g/100g).Minerals result shows that Na (14.835mg/g), Ca (22.570mg/100g) and Mg (3.351mg/100g) were significantly (P<0.05) higher in sample EGU. Sample SES was significantly higher in K (55.855mg/100g) and Zn (0.308mg/100g), while CAS was significantly lower (P<0.05) in Na (3.45mg/100g), Ca (13.15mg/100g) K, (21.655mg/100g), Zn (0.128mg/100g) and Mg (1.925mg/mg) but has the highest value in P (12,252mg/100g). PUM was significantly higher in Vitamin E (8.270mg/100g), while CAS was significantly higher in vitamin A (7.576UI/g). Sample PUM had the highest Polyphenol and Terpenoid content (106.82mg/g and 1.37mg/g respectively) while sample SES had the highest steroid content (0.92mg/g). In conclusion, this study revealed that the nutrients and antioxidant properties of the “Ogiri” samples vary proportionately. The results can guide farmers, processors, and consumers in making informed decisions regarding seed selection and Ogiri preparation.

An Overview of Microfluidic‐assisted Strategies for Synthesis and Applications of Molecularly Imprinted Polymers

This review gives an overview of using microfluidics in conjunction with molecularly imprinted polymers (MIP), which covers two aspects: on the one hand, on‐chip synthesis of polymer and MIP particles on the nano and the micro scale. This comprises both approaches using two different immiscible solvents and homogeneous matrices to obtain the desired particle morphologies. On the other hand, especially paper‐based microfluidic systems have attracted increasing interest as low‐cost analytical tools that are inherently useful for applying at the point of care. By now, there have been several successful attempts to combine them with MIP (instead of biological recognition systems) and to successfully apply them in environmental samples, food matrices, and for diagnostic applications.

Physiological, morphological and chemical changes in pea seeds under different storage conditions.

The loss of germination, viability, and vigor of seeds under storage conditions are the main causes of the need to multiply the seed material for leguminous crops. For crop establishment, seeds obtained in propagation fields are usually used, and the coating comes from the basic seed. In the case of leguminous species, the seeds quickly lose their viability, and in accordance with international regulations, for legumes, the number of seeds increases only in the first year of propagation. Therefore, the main objective of this study was to assess the effects of variations in the storage period, temperature and humidity on the morphophysiological and chemical traits of two pea seed varieties (Gloriosa and Kelvedon Wonder). The pea seeds were harvested at the end of June 2017, 2018 and 2019 and stored for 32, 20 and 8months at T = 4°C and H = 8%; T = 4°C and H = 12%; T = 8°C and H = 8%; T = 8°C and H = 12%; and T = 22°C and H = 65%. The results of the morphological, chemical, and biochemical analyses showed that the highest germination rate; hypocotyl length; radicle length; lipid content; dietetic fiber content; caloric value; and Ca, Mg, K, Na, Fe and Zn contents were detected in the Gloriosa and KW seeds stored for 8months at 4°C and 8% humidity. Analysis of the experimental data by statistical methods revealed that increasing the storage time had an individual significant negative influence only on the germination rate of both pea varieties and on the hypocotyl length and radicle length of the KW variety, while humidity and temperature variation had individual significant influences on the lipid content. The significant effects of humidity and temperature on the germination rate, hypocotyl length and root length of KW plants were also determined. For the remaining morphophysiological and chemical traits of pea seeds, the individual and combined effects of the factors were not statistically significant. Furthermore, the comparison of means using the Tukey test showed that storage conditions related to temperature and humidity generally used by farmers (T = 22°C × H = 65%) did not significantly affect the majority of the nutritional properties of the pea seeds. However, maintaining pea seeds under these conditions for a longer period of time significantly affects seed germination and vigor.

Influence of milling processing on mineral and proximate composition of maize products

AbstractMaize and maize products are major staples consumed worldwide and contain dietary nutrients essential for human nutrition. Processing methods influence the safety and nutritional quality of maize products. This study investigated the effect of different milling processing factors on the mineral and proximate composition of maize products. The study also estimated the contribution of maize products to daily mineral intake. An atomic absorption spectrophotometer was used to determine the mineral content of samples. Proximate composition was determined using methods of the Association of Official Analytical Chemists. A multiple 24‐h dietary recall was used to estimate daily mineral intake of respondents who consume maize products in a cross‐sectional study. The results obtained showed that milling methods influenced the mineral and proximate compositions of the maize products. Mineral content in the milled maize samples followed the order P > Mg > Zn > Fe. The wet milling method retained the highest Fe and P contents, whereas the dried milled sample showed an increased Mg content. The estimated daily mineral intakes of participants were below the World Health Organization recommended standard limits. The respondents were at risk of deficiency of the minerals Fe and Mg. Public health education on sufficient dietary intake of these essential minerals should be intensified.

Educational Models in Analytical Chemistry Lab: The Story behind Lateral Flow Immunoassays in the Context of COVID-19

Educational Models in Analytical Chemistry Lab: The Story behind Lateral Flow Immunoassays in the Context of COVID-19

Digital Architectural Form Generation Through Pixel System-Driven Image Feature Information

This study analyzes valuable information (image feature information) from pixel-based images to systematize the form generation process utilizing this information. Information in architecture is mainly used as an analytical tool for functional design optimization. However, the Fourth Industrial Revolution and advances in information and communication technology have positioned information as a core value-creating tool. Consequently, there is a growing need to develop methodologies for effectively applying information to architectural design generation. This study combines digital technology with images, which directly influence architectural design, transforming them into numerical information. By systematizing the three-dimensional form generation process using low-level image feature information, it analyzes the relationship between the characteristics of valuable information and the generated forms. This approach helps identify the interrelationships between the characteristics of valuable information and the generated forms, the complementarity needed to mitigate the limitations of valuable information, and the potential for architectural applications of the three-dimensional form generation methodology utilizing image information. This approach reduces labor and enhances architectural aesthetics by instantly generating diverse early design alternatives. Such research can provide a more logical basis for avoiding intuitive judgments during the design decision-making process. It can also lay the groundwork for information-centric design systems in architecture.

Leveraging GIS for sustainable tourism development: A comprehensive spatial approach

Abstract. This paper explores the application of Geographic Information Systems (GIS) as a pivotal tool in the spatial analysis and sustainable development of tourism. By mapping tourism resources, analyzing visitor flows, and planning for accessibility and infrastructure, GIS enables a nuanced understanding and management of tourism's spatial dynamics. We delve into the innovative use of GIS for personalized itinerary planning, augmented reality experiences, safety, risk management, environmental impact assessments, resource management, conservation, stakeholder engagement, and community planning. Through a series of methodical processes, GIS facilitates the visualization of natural and cultural attractions, optimizes visitor experiences, and ensures the sustainability of tourism development. The integration of spatial data with advanced analytical tools supports the creation of dynamic, inclusive, and environmentally responsible tourism strategies. This paper highlights the critical role of GIS in shaping future tourism practices, underlining the importance of spatial analysis in fostering a balanced approach to tourism that benefits local communities, preserves cultural heritage, and minimizes ecological footprints.

From SolarWinds to Kaseya: The rise of supply chain attacks in a digital world

Supply chains today rely heavily on information technologies. Such reliance has encouraged attackers to shift their focus on conducting supply chain attacks, which is expected to become the most common type of cyberattack by 2030. Thus, it is crucial for Information Systems practitioners to gain a deeper understanding of supply chain cybersecurity. To that end, this teaching case demonstrates the importance of supply chain cybersecurity in the digital era drawing on two recent attacks with significant impact on supply chains: SolarWinds and Kaseya. We first discuss different dimension of cyberattacks, followed by an introduction of supply chain attacks. We then introduce an analytical tool called cyber kill chain that is widely used for analysing different stages of a cyberattack. In addition, we propose a taxonomy of cyberattacks that can be used as a tool, alongside other tools, to analyse cyberattacks. The taxonomy is especially useful for conducting a lightweight analysis and presenting an overview of cyberattacks to non-technical stakeholders, especially executives and directors.

Kyanite-muscovite-dumortierite vein mineralization mechanisms from advanced microstructural analysis using EBSD

Abstract Dumortierite, an aluminous borosilicate mineral, is relatively rare in Earth’s crust, but it is the second most abundant aluminous borosilicate after tourmaline. Boron is an element with many uses in modern societies worldwide, from health products to wind turbine blades for clean energy, but of limited availability and at future risk of supply. Only a limited number of studies have been published on dumortierite mineralization processes and the factors that control its abundance and distribution remain poorly understood. Here we present the first comprehensive electron backscatter diffraction (EBSD) study of dumortierite mineralization mechanisms in kyanite-muscovite-dumortierite veins occurring in the metapelites of the Amgaon Gneiss Supracrustals, in the Girola hill area, Sakoli region, Central India. Advanced microstructural and chemical analyses show that mixed-mode brittle-viscous deformation in kyanite, by fracturing and easy glide on (100) [001] slip system, facilitates fluid-rock interactions with reactive hydrothermal fluids rich in B, F, and K and containing Na, Ti, Mg, Fe and Pt. These interactions cause the dissolution of kyanite along fracture and cleavage surfaces and the precipitation of muscovite (F = 0.32 wt %) and topaz (F = 16.48 wt %). The motion of ripplocation defects in muscovite facilitates fluid migration along cleavage surfaces and crystallisation of dumortierite needles within these surfaces. Fluid flux removes silica in solution from the system, so reactions may continue. The observed mineral assemblage, the microstructural signature of kyanite and muscovite, the moderate fluorine content of topaz, and low fluorine content of muscovite, together suggest that dumortierite mineralization results from hydrothermal activity, possibly in a transitional magmatic-hydrothermal environment, likely at P > 2.5 kbar and 400°<T < 550°, that could be linked with granite intrusions in the area. Using EBSD we demonstrate that dumortierite mineralization is focussed along muscovite basal cleavage surfaces and dumortierite needle elongation is likely controlled by the fluid flux direction. These new results advance our understanding of dumortierite mineralization mechanisms and conditions and have important implications for our understanding of the distribution of this aluminous borosilicate mineral in muscovite-rich rocks.

Systematic characterization of extracellular vesicles from potato (Solanum tuberosum cv. Laura) roots and peels: biophysical properties and proteomic profiling

IntroductionExtracellular vesicles (EVs) facilitate inter and intra-species/kingdom communication through biomolecule transfer, including proteins and small RNAs. Plant-derived EVs, a hot topic in the field, hold immense capability both as a potential biomarker to study plant physiology and as a biomaterial that can be mass-produced to be used in various industries ranging from cosmetics and food additives to biological pesticides. However, a systematic characterization of plant EVs is required to establish a foundation for further applications and studies.MethodsIn this study, EVs were enriched from hydroponically cultivated potato plants (Solanum tuberosum, cv. Laura). We isolated EVs from root exudates and the apoplastic wash of potato peels using vacuum infiltration. These EVs were then systematically characterized for their biophysical and chemical properties to compare with standard EV characteristics and to explore their roles in plant physiology.ResultsBiophysical and chemical analyses revealed morphological similarities between potato root and peel-derived EVs. The average diameter of root-derived EVs (164.6 ± 7.3 nm) was significantly larger than that of peel-derived EVs (132.2 ± 2.0 nm, p < 0.004). Liquid chromatography–mass spectrometry (LC-MS) demonstrated substantial protein enrichment in purified EVs compared to crude samples, with a 42% enrichment for root EVs and 25% for peel EVs. Only 11.8% of the identified proteins were common between root and peel EVs, with just 2% of significantly enriched proteins shared. Enriched pathways in both EV proteomes were associated with responses to biotic and abiotic stress, suggesting a defensive role of EVs in plants.DiscussionWith further experimentation to elucidate the specific methods of communication, these findings increase the details known about plant EVs in terms of their physical and chemical characteristics and their potential functions, aiding in sustainable agricultural waste utilization for large-scale EV production, aligning with the concept of “valorization”.

COMPETENCE AND TEACHER PERFORMANCE: AN ANALYSIS OF THE MODERATING ROLE OF JOB SATISFACTION

This study aims to examine the effect of competence on performance, with job satisfaction as a moderator, among vocational high school teachers in Pekanbaru City. The approach used is quantitative, with the research population consisting of all vocational high school teachers in Pekanbaru City, totaling 778 individuals. Based on the Krejcie and Morgan table (1970), the sample size is 260 individuals, selected through Systematic Random Sampling. Primary data were collected through a questionnaire using a 1-5 point Likert scale and processed using Structural Equation Modeling (SEM) with Smart PLS 3.0 as the analytical tool. The results of hypothesis testing indicate that: 1) competence has a positive and significant effect on performance, 2) job satisfaction also has a positive and significant effect on performance, and 3) job satisfaction moderates the effect of competence on teacher performance.

Artificial intelligence, emotional labor, and the quest for sociological and political imagination among low-skilled workers

Abstract This study examines how generative AI impacts low-skilled workers in their daily professional lives, how it changes the nature of their work, and what, if any, strategies they develop to cope with this new reality. Emphasis is placed on call center agents—an occupational group facing a particularly high automation risk. Drawing on Constructivist Grounded Theory and semistructured interviews in an Austrian call center, we uncover how flawed generative AI tools have increased emotional labor among these workers. This increase is hypothesized to result in agents’ inability to embed their own problems in the larger social context of generative AI’s impact on the labor market, let alone to politicize these problems. They were thus said to lack sociological and political imagination. Our study is the first to link emotional labor with these forms of imagination among low-skilled workers, offering new analytical tools for future research on generative AI’s nuanced effects on the labor market. To empower low-skilled workers, foster their imaginations and address their concerns, we propose several policy recommendations, including targeted education campaigns, enhanced social dialogue, co-determination rights, and tailored upskilling programs. This study thus offers a valuable contribution to scientific research while providing practical implications for policymakers.

Network analysis: An overview for mental health research.

Network approaches to psychopathology have become increasingly common in mental health research, with many theoretical and methodological developments quickly gaining traction. This article illustrates contemporary practices in applying network analytical tools, bridging the gap between network concepts and their empirical applications. We explain how we can use graphs to construct networks representing complex associations among observable psychological variables. We then discuss key network models, including dynamic networks, time-varying networks, network models derived from panel data, network intervention analysis, latent networks, and moderated models. In addition, we discuss Bayesian networks and their role in causal inference with a focus on cross-sectional data. After presenting the different methods, we discuss how network models and psychopathology theories can meaningfully inform each other. We conclude with a discussion that summarizes the insights each technique can provide in mental health research.