Search Results (2,906)

Leucas nubica Benth. (Lamiaceae) is an annual herbaceous plant, native to east and northeast tropical Africa. The whole plant is renowned for the treatment of jaundice. The present study aimed at an in-depth phytochemical profiling and evaluation of in vitro antioxidant and enzyme inhibitory potential of methanol–aqueous extract from L. nubica aerial parts. The liquid chromatography–high-resolution mass spectrometry (LC-HRMS) experiment revealed more than 70 secondary metabolites, including carboxylic and phenolic acids, phenylethanoid, iridoid, and lignan glycosides, and flavonoids. The L. nubica extract profile was dominated by the phenylethanoid glycoside verbascoside. All annotated compounds are reported for the first time in the species. The extract actively scavenged DPPH and ABTS radicals (38.8 ± 0.1 and 36.8 ± 0.4 mg TE/g) and showed high CUPRAC (71.1 ± 1.1 mg TE/g) and moderate FRAP (44.9 ± 2.6 mg TE/g) reducing power. The L. nubica extract exhibited high inhibition towards acetylcholinesterase (2.23 ± 0.02 mg GALAE/g), butyrylcholinesterase (2.38 ± 0.04 mg GALAE/g), and tyrosinase (60.7 ± 0.6 mg KAE/g). The obtained results highlight L. nubica extract as a rich source of phenylethanoid glycosides and flavonoids with significant bioactivity and shed light into the phytochemical composition and pharmacological potential of the plant. Full article

This study examines how employee benefit practices link employee well-being with financial sustainability in sustainable organization management. Focusing on Generation Z, it investigates the intersection between meaning attributed to employee benefits and managerial decision-making guided by financial rationality. Drawing on human resources management (HRM) and finance perspectives, employee benefits are conceptualized as mechanisms for balancing human-centered value creation and economic resilience. A qualitative design was used, based on semi-structured interviews with 15 Generation Z employees and 20 human resources (HR) and finance managers in Türkiye. Data were analyzed through thematic analysis and the Gioia methodology to develop an inductive, multi-level framework. The findings indicate that Generation Z employees view employee benefits as psychosocial resources reflecting justice, autonomy, psychological safety, and value alignment—core components of subjective and eudaimonic well-being—while managers assess them primarily through financial sustainability logics such as cost control and return on investment. Overall, meaning- and cost-oriented perspectives emerge as mutually reinforcing within sustainable organizational systems. The study proposes the Meaning–Cost Balance (MCB) Framework, conceptualizing employee benefits as a strategic management mechanism aligning employee well-being with financial resilience. Positioned at the intersection of HRM and financial sustainability, the framework contributes to sustainable organization management and offers a transferable basis for future comparative research. Full article

This study demonstrates that high-performance work systems (HPWSs)—encompassing selective staffing, extensive training, performance incentives, and employee participation—significantly enhance the dimensions of psychological empowerment, including meaning, competence, self-determination, and impact, thereby fully mediating a stronger stay intention. Leader–member exchange (LMX) amplifies both HPWS-to-empowerment and empowerment-to-stay intention pathways via dyadic trust, while team–member exchange (TMX) strengthens initial resource uptake. Theoretically, based on social exchange theory, the results enhance relational exchange frameworks by emphasizing LMX’s superior function over TMX in high-contact situations, positioning empowerment as the critical mechanism connecting HRM practices to loyalty in service sectors. The cornerstones of sustainable hospitality development include employee-centric strategies that foster empowerment through value-aligned jobs, certifications that enhance skills, independent guest service decision-making, and feedback loops that transform HPWSs into long-lasting retention engines by integrating TMX peer networks for cooperative support with LMX through individualized coaching and feedback that fosters trust. By reducing attrition, stabilizing talent pipelines, and stimulating service quality innovation, these tactics promote robust operations and sustained competitiveness. Full article

The use of styrylium dyes as organic nonlinear optical materials in many photonics domains has been the subject of research for decades. It has been noted that over time, research has also looked into the biological activity of styrylium dyes, namely their antibacterial effects, as well as attempts to establish links between structure and property by choosing particular structural pieces. These investigations’ scope is still very limited. Therefore, our main goal was to synthesize a styrylium compound with antimicrobial potential. A novel styrylquinolinium compound (D) was synthesized using Knoevenagel condensation. Spectroscopic techniques, including IR, 1D and 2D NMR (COSY, HSQC, and HMBC), HRMS spectra, and X-ray analysis, were used to confirm its structure. The antimicrobial and anti-inflammatory activity of the compound was assessed. The compound was found to have very good antimicrobial activity against five Gram-positive strains, three Gram-negative strains, and fungi. The most pronounced effect of the compound was against Escherichia coli and Pseudomonas aeruginosa. The compound’s anti-inflammatory activity was evaluated through its ex vivo immunohistochemistry. DFT calculations, such as geometry optimization, Molecular Electrostatic Potential (MEP), HOMO–LUMO, reactivity parameters and molecular docking simulation were applied to investigate the electronic features of the compound and confirm the biological activity. The compound (D) demonstrated a promising antibacterial and immunomodulatory profile. Its ability to induce IL-1β and at the same time moderately reduce NOS3 can be considered as a controlled adaptation of the immune response, especially in cases requiring local immune activation. Docking simulation revealed that (D) binds effectively to the active site of the bacterial protein, supporting the experimental findings of the compound’s antibacterial activity. Full article

Indane-1,3-dione and 1,4-dihydropyridine (1,4-DHP) scaffolds are of significant interest in medicinal chemistry. Herein, we report the synthesis characterization of a new lipid-like indane-1,3-dione–1,4-DHP betaine, 2-(3′,5′-bis((dodecyloxy)carbonyl)-2′,6′-dimethyl-1′,4′-dihydro-[3,4′-bipyridin]-1-ium-1-yl)-1,3-dioxo-2,3-dihydro-1H-inden-2-ide (3). Compound 3 was synthesized from 2,2-dicyanomethylideneindan-1,3-dione (1) oxide and a didodecyl-substituted 1,4-DHP derivative 2 and characterized by UV–Vis spectroscopy, ¹H-NMR, ¹³C-NMR, and HRMS. The obtained results demonstrate a promising strategy for the design of delivery agents, exploiting the lipid-like properties of the synthesized betaine. Full article

Artificial intelligence (AI) is increasingly reshaping organizational dynamics, not only through efficiency gains but by influencing how work is structured, interpreted, and experienced. In healthcare, where professional team stability is crucial, this transformation intersects with structural issues such as persistent nurse turnover. This study presents an exploratory case study of a private accredited hospital in Italy that introduced an AI-enabled shift scheduling system (“Dream-Shift”) in response to perceived inequities and workforce instability. The system was embedded in a participatory architecture that included a Nursing Practice Council and HR dashboards to visualize staffing patterns. Drawing on theories of Sustainable Human Resource Management (SHRM), algorithmic management, and people sustainability, the study examines how AI-mediated transparency and participation affect fairness perceptions, predictability, and organizational climate. Using administrative data, ethnographic observations, internal documents, and informal feedback, the study finds that the algorithm did not eliminate all inequities but made decision constraints visible and debatable. It redistributed the emotional burden of scheduling and enabled more structured conversations about work. Managers transitioned from unilateral decision-makers to facilitators of collective interpretation. The results suggest that when integrated into participatory infrastructures, AI can foster organizational transparency, support relational stability, and act as a socio-technical enabler of people sustainability rather than as a tool of control. Full article

Micro-foundational HRM has advanced our understanding of how employees perceive and respond to HR practices, yet explanations of how HR systems can generate and sustain coordinated action in day-to-day work remain underspecified. This article presents a theory-building integrative review that specifies a constrained, generative mechanism grounded in observable interaction episodes. We propose a functional architecture that assigns constructs to distinct explanatory roles: enabling states (Role A), interaction episodes as the behavioral engine (Role B), and emergent coordination products (Role C). Psychological safety is positioned as an enabling condition that shifts the likelihood and quality of enactment, whereas collective leadership behavior (CLB) is defined as response-inclusive influence episodes (an influence attempt plus an observable response such as uptake, contestation, neglect, or sanction). We formalize a recursive safety–CLB cycle in which response patterns update subsequent safety and influence dispersion over time, which can yield divergent coordination trajectories even when HR conditions are broadly similar. The framework generates discriminant predictions about response profiles, dispersion versus centralization of influence, and temporal signatures, and it clarifies minimal design requirements for testing recursion with episode-level and intensive longitudinal evidence. We discuss implications for micro-foundational HRM, measurement alignment, and testable design-relevant implications for HR system design as an interaction-relevant cue environment. Full article

Neuropathic pain (NP) arises from maladaptive changes in peripheral and central nociceptive circuits, yet molecular alterations spanning the entire pain neuraxis remain poorly understood. Neuroinflammation is increasingly recognized as a central mechanism in NP chronification, yet the region-specific molecular events linking immune activation to affective pain processing remain inadequately defined. In this study, we employed high-resolution LC-HRMS-based quantitative proteomics to investigate chronic constriction injury (CCI)-induced molecular alterations in the sciatic nerve (SN), spinal cord (SC), and orbitofrontal cortex (OFC) of male Wistar rats, a region critical for affective and cognitive pain modulation. Behavioral assessments confirmed the development of NP phenotypes and motor deficits. Proteomic profiling revealed exclusive and differentially expressed proteins enriched in neuroinflammatory pathways across all regions. S100 proteins (S100A8 and S100B) were significantly elevated in SN, SC, and OFC, as confirmed by immunofluorescence. Their up-regulation coincided with increased astrocyte (GFAP) and microglial (Iba-1) activation, highlighting a pervasive inflammatory milieu. Intriguingly, the OFC proteome demonstrated marked up-regulation of dopamine-regulating proteins and positive regulation of dopaminergic neurotransmission, suggesting involvement of reward-related analgesic circuits. Together, our findings delineate a “nociceptive neuraxis” driven by neuroimmune activation and neuromodulatory adaptations that interfaces with dopaminergic signaling to influence sensory and affective components of pain. This integrative molecular map highlights potential therapeutic targets, including glial-derived S100 proteins and dopamine modulators for the comprehensive management of NP. Full article

Within the framework of green chemistry and wild fruit valorization, this study optimizes the extraction of bioactive compounds from Prunus spinosa L. fruits using glycerin-based ultrasound-assisted extraction (UAE). Response Surface Methodology (RSM) and Artificial Neural Networks (ANN) were comparatively employed to model the process. Significant improvements in extraction efficiency were achieved, with total phenolic content increasing from 9.28 to 23.22 mg GAE/g DW, total flavonoid content from 6.53 to 21.65 mg CE/g DW, and antioxidant activity (DPPH assay) from 57.04% to 86.34%. While both models performed well, ANN demonstrated slightly higher predictive accuracy, highlighting its potential for capturing complex, non-linear relationships in the extraction process. We identified the optimal extraction conditions as 9 min extraction time, 100% ultrasonic amplitude, and 40% water in glycerin, and these conditions were experimentally validated. UHPLC-DAD-HRMS/MS profiling revealed a rich phytochemical fingerprint dominated by phenolic acids, caffeoylquinic acid derivatives, and flavonol glycosides, and revealed largely overlapping qualitative phytochemical profiles between hydroglyceric and ethanolic extracts. Comparative extraction using 70% ethanol under identical conditions resulted in lower TPC, TFC, and antioxidant activity, indicating the improved efficiency of glycerin under the investigated conditions. Overall, the optimized glycerin-based UAE provides a sustainable, food-safe approach for extracting bioactive compounds from underutilized P. spinosa fruits. These results support its application in functional foods and in nutraceutical and cosmetic formulations. Full article

A hybrid two-route strategy for converting Cornus mas L. stones into bioactive and other high-value compounds was developed and thoroughly evaluated. In Route 1, microwave-assisted extraction (MAE) is applied directly to the stones biomass following an experimental design created with Design Expert 11. Route 2 involves Soxhlet n-hexane extraction of the raw biomass, followed by MAE of the resulting defatted residue. The efficiency of the two routes was evaluated by comparing total polyphenol, flavonoid, and saponin content (TPC, TFC, TSC) and antioxidant activity (AA) of all obtained extracts, the fatty acid composition of MAE (route 1) and Soxhlet n-hexane extracts, and the metabolite composition of MAE extracts recovered in Route 1 and Route 2. The series of analyses performed involved GC–FID fatty acid profiling and composition determination using HPLC-HRMS/MS. These analyses showed that Soxhlet oil yield was 4.00 ± 0.18% with low AA, whereas subsequent MAE extracts had higher TPC, TFC, and TSC and 1.7-fold higher ABTS values than those of MAE Route 1. The increased AA is likely a result of the higher overall phenolic content, especially the presence of the potent antioxidant methyl gallate, which was not detected in MAE Route 1 extract, and not identified in C. cherry stones until now. Our results show that the CCD-optimized hybrid strategy effectively maximizes the recovery of bioactive compounds, demonstrates the superior potential of Route 2 for obtaining antioxidant-rich extracts, and widens the extent of applications of the underused C. cherry stone biomass. Full article

The growing use of AI-supported recruitment systems raises concerns related to model opacity, auditability, and ethically sensitive decision-making, despite their predictive potential. In human resource management, there is a clear need for recruitment solutions that combine analytical effectiveness with transparent and explainable decision support. Existing approaches often lack coherent, multi-layered architectures integrating expert knowledge, machine learning, and interpretability within a single framework. This article proposes an interpretable, multi-layered recruitment model designed to balance predictive performance with decision transparency. The framework integrates an expert rule-based screening layer, an unsupervised clustering layer for structuring candidate profiles and generating pseudo-labels, and a supervised classification layer trained using repeated k-fold cross-validation. Model behavior is explained using SHAP, while Necessary Condition Analysis (NCA) is applied to diagnose minimum competency thresholds required to achieve a target quality level. The approach is demonstrated in a Data Scientist recruitment case study. Results show the predominance of centroid-based clustering and the high stability of linear classifiers, particularly logistic regression. The proposed framework is replicable and supports transparent, auditable recruitment decisions. Full article

Detection of hazardous substances in feed is important for ensuring human health. A method based on liquid chromatography-high-resolution mass spectrometry (LC-HRMS) was developed and validated for the screening and confirmation of 420 hazardous substances, including pesticides, veterinary drugs, and mycotoxins commonly found in feed. The screening phase employed less stringent criteria to minimize false negatives caused by matrix effects. Subsequently, stricter identification criteria were applied for confirmation to avoid false positives from interfering compounds. The performance of the proposed method was verified by limit of detection (LOD, 5~500 μg/L), screening detection limits (SDL, 50~500 μg/L), matrix effect (ME, 36.12~121.16%), precision (0.02~14.98%), stability, and accuracy. The method was successfully applied to real feed samples, demonstrating its capability to detect the presence of the 420 target hazardous substances. We believe our method provides strong technical support for ensuring the quality and safety of feed. Full article

Water represents the fundamental source of life for all human and animal populations; however, its consumption has become increasingly hazardous due to high levels of pollution. Modern agricultural practices rely heavily on pesticides, which significantly contribute to water contamination and imbalances in aquatic ecosystems. Moreover, another critical category of pollutants consists of pathogenic bacteria that proliferate in aquatic environments, mainly originating from hospital and urban wastewater because of human activity. Considering these major environmental and health challenges, the present study aims to develop an optimized method for water treatment by synthesizing magnetic silica-based aerogels using a microfluidic vortex chip and systematically varying synthesis parameters to enhance material performance. The physicochemical properties of the aerogels were characterized using XRD, FTIR, SEM, EDS, and BET. The pesticide adsorption capacity of the materials was evaluated using FT-ICR HR-MS analysis, which demonstrated the high efficiency of the aerogels in removing a complex mixture of pesticides. In parallel, antimicrobial efficacy was assessed against E. faecalis, E. coli, and P. aeruginosa isolated from surface water, hospital wastewater, and the influent of a well-known wastewater treatment plant in Bucharest, as well as against ATCC reference strains. Additionally, the study investigated the biocompatibility and biological responses of magnetic aerogels using MTT assays, nitric oxide production, lactate dehydrogenase release, intracellular ROS levels, and quantification of total protein, malondialdehyde, and reduced glutathione in HaCaT and HEK293 cell lines. The results confirm the efficiency and application potential of the developed materials and emphasize the importance of optimizing synthesis to achieve high-performance aerogels for effective decontamination of polluted waters. Full article

Glycogen synthase kinase-3 beta (GSK-3β) is a multifunctional serine/threonine kinase mediating multiple cellular functions, such as differentiation, apoptosis, and cell proliferation. Because of their ability to alter carcinogenic pathways, GSK-3β inhibitors are being explored for the development of anticancer molecules. In the present study, we synthesized and evaluated the cytotoxic properties of a series of twenty indole–triazole-linked pyrazolone derivatives, 10Aa–Ed. All derivatives were characterized by FTIR, ¹H/¹³C NMR, and high-resolution mass spectrometry (HRMS) methods. All compounds and standards, sunitinib and 5-Fluorouracil (5-FU), were screened against four adherent cell lines, including pancreatic adenocarcinoma (Capan-1), colorectal carcinoma (HCT-116), glioblastoma(LN229), and lung carcinoma (NCI-4460), and four non-adherent cell lines, including acute myeloid leukemia (HL-60), chronic myeloid leukemia (K562), T lymphoblast (MOLT4), and non-Hodgkin lymphoma (Z138). Among the screened derivatives, molecule 10Aa showed cytotoxicity against MOLT 4, Z138, and HL60 with CC₅₀ values of 14.45 μM, 15.34 μM, and 17.56 μM, respectively. GSK-3β kinase inhibition was evaluated with the 10Aa, which is capable of inhibiting GSK-3β in a dose-dependent manner. Additionally, molecular docking was performed to estimate the correlation between invitro data and GSK-3β binding affinity. The outcomes of the invitro experiments demonstrated strong concordance with the insilico data. The discovery yielded compounds 10Aa and 10Cd, which can be modified to create effective anticancer agents that target GSK-3β. Full article

Bongkrekic acid (BKA), a highly lethal toxin, has been implicated in frequent poisoning incidents in recent years, posing a serious threat to global food safety and creating an urgent need for rapid and sensitive detection methods. This review provides a systematic analysis of the entire BKA detection technologies, covering sample pretreatment techniques, instrumental analysis, immunoassays, and biosensing methods. It assesses the merits of key methods and also explores the strategic cross-application of detection paradigms developed for analogous toxins. This review delivers a comprehensive and critical evaluation of BKA detection technologies. First, it discusses sample pretreatment strategies, notably solid-phase extraction (SPE) and QuEChERS. Subsequently, it analyzes the principles, performance, and applications of core detection methods, including high-performance liquid chromatography–tandem mass spectrometry (HPLC-MS/MS), high-resolution mass spectrometry (HRMS), time-resolved fluorescence immunoassay (TRFIA), dual-mode immunosensors and nanomaterial-based sensors. Instrumental methods (e.g., HRMS) offer unmatched sensitivity [with a limit of detection (LOD) as low as 0.01 μg/kg], yet remain costly and laboratory-dependent. Immunoassay and biosensor approaches (TRFIA and dual-mode sensors) enable rapid on-site detection with high sensitivity (ng/mL to pg/mL), though challenges in stability and specificity remain. Looking forward, the development of next-generation BKA detection could be accelerated by cross-applying cutting-edge strategies proven for toxins—such as Fumonisin B1 (FB1), Ochratoxin A (OTA), and Aflatoxin B1 (AFB1)—including nanobody technology, CRISPR-Cas-mediated signal amplification, and multimodal integrated platforms. To translate this potential into practical tools, future research should prioritize the synthesis of high-specificity recognition elements, innovative signal amplification strategies, and integrated portable devices, aiming to establish end-to-end biosensing systems capable of on-site rapid detection through multitechnology integration. Full article