Search Results (2,617)

pH is a critical parameter requiring precise monitoring across scientific, industrial, and biological domains. Fluorescent pH probes offer a powerful alternative to traditional methods (e.g., electrodes, indicators), overcoming limitations in miniaturization, long-term stability, and electromagnetic interference. By utilizing photophysical mechanisms—including intramolecular charge transfer (ICT), photoinduced electron transfer (PET), and fluorescence resonance energy transfer (FRET)—these probes enable high-sensitivity, reusable, and biocompatible sensing. This review systematically details recent advances, categorizing probes by operational pH range: strongly acidic (0–3), weakly acidic (3–7), strongly alkaline (>12), weakly alkaline (7–11), near-neutral (6–8), and wide-dynamic range. Innovations such as ratiometric detection, organelle-specific targeting (lysosomes, mitochondria), smartphone colorimetry, and dual-analyte response (e.g., pH + Al³⁺/CN⁻) are highlighted. Applications span real-time cellular imaging (HeLa cells, zebrafish, mice), food quality assessment, environmental monitoring, and industrial diagnostics (e.g., concrete pH). Persistent challenges include extreme-pH sensing (notably alkalinity), photobleaching, dye leakage, and environmental resilience. Future research should prioritize broadening functional pH ranges, enhancing probe stability, and developing wide-range sensing strategies to advance deployment in commercial and industrial online monitoring platforms. Full article

Natural fiber-based biocomposites are rapidly gaining traction in sustainable manufacturing. However, their supply chain (SC) designs at the feedstock pre-processing stage often lack robust multicriteria decision-making evaluations, which can impact downstream processes and final product quality. This case study proposes a sustainability-driven multicriteria decision-making framework for selecting pre-processing equipment configurations within a hemp-based biocomposite SC. Using a cradle-to-gate system boundary, four alternative configurations combining balers (square vs. round) and hammer mills (full-screen vs. half-screen) are evaluated. The analytical network process (ANP) model is used to evaluate alternative SC configurations while capturing the interdependencies among environmental, economic, social, and technical sustainability criteria. These criteria are further refined with the inclusion of sub-criteria, resulting in a list of 11 key performance indicators (KPIs). To evaluate ranking robustness, a non-linear programming (NLP)-based sensitivity model is developed, which minimizes the weight perturbations required to trigger rank reversals, using an IPOPT solver. The results indicated that the Half-Round setup provides the most balanced sustainability performance, while Full-Square performs best in economic and environmental terms but ranks lower socially and technically. Also, the ranking was most sensitive to the weight of the system reliability and product quality criteria, with up to a 100% shift being required to change the top choice under the ANP model, indicating strong robustness. Overall, the proposed framework enables decision-makers to incorporate uncertainty, interdependencies, and sustainability-related KPIs into the early-stage SC design of bio-based composite materials. Full article

In today’s dynamic and highly uncertain environment, organizations, particularly in the aviation sector, face increasing challenges that demand resilient, flexible, and data-driven change management decisions. Responding to the growing need for structured approaches to managing complex uncertainties—geopolitical tensions, economic volatility, social shifts, rapid technological advancements, environmental pressures and regulatory changes—this research proposes a theoretical change management model for aviation service providers, such as airports. Integrating three analytical approaches, the model offers a robust, multi-method approach for supporting sustainable transformation under uncertainty. Normative analysis using Bayesian decision theory identifies influential external environmental factors, capturing probabilistic relationships, and revealing causal links under uncertainty. Prescriptive planning through scenario theory explores alternative future pathways and helps to identify possible predictions, offer descriptive evaluation employing fuzzy comprehensive evaluation, and assess decision quality under vagueness and complexity. The proposed four-stage model—observation, analysis, evaluation, and response—offers a methodology for continuous external environment monitoring, scenario development, and data-driven, proactive change management decision-making, including the impact assessment of change and development. The proposed model contributes to the theoretical advancement of the change management research area under uncertainty and offers practical guidance for aviation organizations (airports) facing a volatile external environment. This framework strengthens aviation organizations’ ability to anticipate, evaluate, and adapt to multifaceted external changes, supporting operational flexibility and adaptability and contributing to the sustainable development of aviation services. Supporting aviation organizations with tools to proactively manage systemic uncertainty, this research directly supports the integration of sustainability principles, such as resilience and adaptability, for long-term value creation through change management decision-making. Full article

The search for sustainable, economically viable, and effective plant protection strategies against pathogenic bacteria, fungi, and viruses is a major challenge in modern agricultural practices. Chitosan (CS) is an abundant cationic natural biopolymer known for its biocompatibility, low toxicity, and antimicrobial properties. Its potential use in agriculture for pathogen control is a promising alternative to traditional chemical fertilisers and pesticides, which raise concerns regarding public health, environmental protection, and pesticide resistance. This study focused on the preparation of chitosan nanoparticles (CS-NPs) through cross-linking with organic molecules, such as tannic acid (TA). Various formulations were explored for the development of stable nanoscale particles having encapsulation capabilities towards low compounds of varying polarity and with potential agricultural applications relevant to plant health and growth. The solution properties of the NPs were assessed using dynamic and electrophoretic light scattering (DLS and ELS); their morphology was observed through atomic force microscopy (AFM), while analytical ultracentrifugation (AUC) measurements provided insights into their molar mass. Their properties proved to be primarily influenced by the concentration of CS, which significantly affected its intrinsic conformation. Additional structural insights were obtained via infrared and UV–Vis spectroscopic measurements, while detailed fluorescence analysis with the use of three different probes, as model cargo molecules, provided information regarding the hydrophobic and hydrophilic microdomains within the particles. Full article

Background: Depression that is resistant to two or more adequate treatment trials—treatment-resistant depression (TRD)—is a prevalent clinical challenge. Although psychotherapies have been recommended by clinical guidelines as an alternative or adjunctive treatment strategy, the effectiveness of psychotherapy in individuals with TRD has not yet been evaluated through meta-analytic methods, primarily due to a limited number of trials. This highlights the necessity of personalized research targeting this specific population. This systematic review and meta-analysis aimed to summarize the evidence on psychotherapy in treating TRD. Methods: A systematic search was conducted following the Guidelines from Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Articles were included if they quantitatively examined the efficacy of psychotherapy on depression symptoms in individuals diagnosed with depression who had not responded to at least two prior treatments (i.e., pharmacotherapy and/or psychotherapy). Results: A total of 12 studies were included. The quality of evidence was evaluated as being globally moderate. When pooling all psychotherapies, a small-to-moderate, but significant, effect on depressive symptoms was observed compared to the control group (SMD = −0.49, CI = −0.63; −0.34). The observed effect remained unchanged after removing the outlier (SMD = −0.47, CI = −0.62; −0.32). When examining depressive symptoms by type of psychotherapy, Mindfulness-Based Cognitive Therapy (SMD = −0.51, CI = −0.76; −0.25), Cognitive Behavioral Therapy (SMD = −0.53, CI = −0.92; −0.14), and Cognitive Therapy (SMD = −0.51, CI = −1.01; −0.01) showed a moderately significant effect on depressive symptoms compared to the control group. Conclusions: Although this potentially represents the first meta-analysis in this area, the number of studies specifically addressing this complex population remains limited, and the existing literature is still in its early stages. Research focusing on TRD is notably sparse compared to the broader body of work on depression without treatment resistance. Consequently, it was not possible to conduct meta-analyses by type of psychotherapy across all treatment modalities and by type of control group. Due to several study limitations, there is currently limited evidence available about the effectiveness of psychotherapy for TRD, and further trials are needed. Beyond the treatments usually offered for depression, it is possible that TRD requires a personalized medicine approach. Full article

Background/Objectives: Conventional blood collection can be challenging in a non-clinical or home-based setting. In response, vacuum-assisted lancing devices for capillary blood collection (typically from the upper arm) have gained popularity to broaden access to diagnostic testing. However, these devices are often costly relative to the reimbursement rate for common laboratory testing panels. This study describes the design and evaluation of Comfort Draw™, a simplified and economical vacuum-assisted capillary blood collection device. Methods: Comfort Draw™ was evaluated by 12 participants in a preliminary study and by 42 participants in a follow-up study. Metrics assessed included the following: vacuum pressure of the device, skin temperature generated by the Comfort Draw prep warmer, blood collection volume, and analytical accuracy (for 19 common serum-based analytes). Results: Acceptable blood volume (>400 µL) and serum volume (>100 µL) were collected by Comfort Draw in 85.5% and 95.1% of cases, respectively. Seventeen of the nineteen analytes examined were within CLIA acceptance limits compared to matched venous samples. Self-reported pain scores associated with Comfort Draw collection averaged 0.39 on a scale from 0 to 10. Conclusions: In this preliminary clinical study, Comfort Draw was found to be a valid and relatively painless method for collecting capillary blood specimens. The device’s simple design and lower cost could enable broader applications compared to more complex alternative capillary blood collection devices. Full article

This study arises from the search for non-invasive diagnostic alternatives for equine gastric ulceration (EGUS), which is prevalent, clinically variable and only confirmed by gastroscopy. The aim is to quantify five salivary biomarkers (IL1-F5, PIP, CA VI, serotransferrin, albumin) under clinical conditions by validated assays and analyse their diagnostic value. Horses were grouped in No EGUS (neither clinical signs of EGUS nor gastric lesions), EGUS non-clinical (apparently no clinical signs of EGUS but with gastric lesions), and EGUS clinical (obvious clinical signs of EGUS and with gastric lesions). The concentration of 5 analytes could be quantified using sandwich ELISA assays, with high precision (CV: 6.79–12.38%) and accuracy (>95%). Mean salivary levels of IL1-F5, CA-VI, serotransferrin and albumin were significantly higher in EGUS clinical horses compared to No EGUS horses, whereas PIP showed no statistical significance. EGUS non-clinical horses showed statistical differences with No EGUS horses for PIP and albumin. In addition, IL1-F5, CA-VI, serotransferrin and albumin showed moderate accuracy to distinguish between No EGUS and EGUS clinical horses (AUC ≥ 0.8), with sensitivity and specificity greater than 77% and 65%, respectively. Therefore, these biomarkers could be a promising starting point for screening horse that might have EGUS in practice. Full article

Tocopherols, major lipid-soluble components of vitamin E, are essential natural products with significant nutritional and pharmacological value. Their structural diversity and uneven distribution across vegetable oils require accurate analytical strategies for compositional profiling, quality control, and authenticity verification, amid concerns over food fraud and regulatory demands. Analytical challenges, such as matrix effects in complex oils and the cost trade-offs of green extraction methods, complicate these processes. This review examines recent advances in tocopherol analysis, focusing on extraction and detection techniques. Green methods like supercritical fluid extraction and deep eutectic solvents offer selectivity and sustainability, though they are costlier than traditional approaches. On the analytical side, hyphenated techniques such as supercritical fluid chromatography-mass spectrometry (SFC-MS) achieve detection limits as low as 0.05 ng/mL, improving sensitivity in complex matrices. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) provides robust analysis, while spectroscopic and electrochemical sensors offer rapid, cost-effective alternatives for high-throughput screening. The integration of chemometric tools and miniaturized systems supports scalable workflows. Looking ahead, the incorporation of Artificial Intelligence (AI) in oil authentication has the potential to enhance the accuracy and efficiency of future analyses. These innovations could improve our understanding of tocopherol compositions in vegetable oils, supporting more reliable assessments of nutritional value and product authenticity. Full article

Halogenated flame retardants have been amongst the most widely used and effective solutions for enhancing fire resistance. However, their use is currently strictly regulated due to serious health and environmental concerns. In this context, phosphorus-based and mineral flame retardants have emerged as promising alternatives. Despite this, their combined use is neither straightforward nor guaranteed to be effective. This study scrutinizes the interactions between these two classes of flame retardants (FR) through a systematic analysis aimed at elucidating the antagonistic pathways that arise from their coexistence. Specifically, this study focuses on two inorganic fillers, mineral huntite and chemically precipitated magnesium hydroxide, both of which produce basic oxides upon thermal decomposition. These fillers were incorporated into a poly(butylene terephthalate) (PBT) matrix to be utilized as advanced-mattress FR coating fabric and were subjected to a series of flammability tests. The pyrolysis products of the prepared polymeric composite compounds were isolated and thoroughly characterized using a combination of analytical techniques. Thermogravimetric analysis (TGA) and differential thermogravimetric analysis (dTGA) were employed to monitor decomposition behavior, while the char residues collected at different pyrolysis stages were examined spectroscopically, using FTIR-ATR and Raman spectroscopy, to identify their structure and the chemical reactions that led to their formation. X-ray diffraction (XRD) experiments were also conducted to complement the spectroscopic findings in the chemical composition of the resulting char residues and to pinpoint the different species that constitute them. The morphological changes of the char’s structure were monitored by scanning electron microscopy with energy dispersive X-ray spectroscopy (SEM-EDS). Finally, the Limited Oxygen Index (LOI) and UL94 (vertical sample mode) methods were used to assess the relative flammability of the samples, revealing a significant drop in flame retardancy when both types of flame retardants are present. This reduction is attributed to the neutralization of acidic phosphorus species by the basic oxides generated during the decomposition of the basic inorganic fillers, as confirmed by the characterization techniques employed. These findings underscore the challenge of combining organophosphorus with popular flame-retardant classes such as mineral or basic metal flame retardants, offering insight into a key difficulty in formulating next-generation halogen-free flame-retardant composite coatings. Full article

Background/Objectives: The RTK-RAS signaling cascade is a central axis in colorectal cancer (CRC) pathogenesis, governing cellular proliferation, survival, and therapeutic resistance. Somatic alterations in key pathway genes—including KRAS, NRAS, BRAF, and EGFR—are pivotal to clinical decision-making in precision oncology. However, the integration of these genomic events with clinical and demographic data remains hindered by fragmented resources and a lack of accessible analytical frameworks. To address this challenge, we developed AI-HOPE-RTK-RAS, a domain-specialized conversational artificial intelligence (AI) system designed to enable natural language-based, integrative analysis of RTK-RAS pathway alterations in CRC. Methods: AI-HOPE-RTK-RAS employs a modular architecture combining large language models (LLMs), a natural language-to-code translation engine, and a backend analytics pipeline operating on harmonized multi-dimensional datasets from cBioPortal. Unlike general-purpose AI platforms, this system is purpose-built for real-time exploration of RTK-RAS biology within CRC cohorts. The platform supports mutation frequency profiling, odds ratio testing, survival modeling, and stratified analyses across clinical, genomic, and demographic parameters. Validation included reproduction of known mutation trends and exploratory evaluation of co-alterations, therapy response, and ancestry-specific mutation patterns. Results: AI-HOPE-RTK-RAS enabled rapid, dialogue-driven interrogation of CRC datasets, confirming established patterns and revealing novel associations with translational relevance. Among early-onset CRC (EOCRC) patients, the prevalence of RTK-RAS alterations was significantly lower compared to late-onset disease (67.97% vs. 79.9%; OR = 0.534, p = 0.014), suggesting the involvement of alternative oncogenic drivers. In KRAS-mutant patients receiving Bevacizumab, early-stage disease (Stages I–III) was associated with superior overall survival relative to Stage IV (p = 0.0004). In contrast, BRAF-mutant tumors with microsatellite-stable (MSS) status displayed poorer prognosis despite higher chemotherapy exposure (OR = 7.226, p < 0.001; p = 0.0000). Among EOCRC patients treated with FOLFOX, RTK-RAS alterations were linked to worse outcomes (p = 0.0262). The system also identified ancestry-enriched noncanonical mutations—including CBL, MAPK3, and NF1—with NF1 mutations significantly associated with improved prognosis (p = 1 × 10⁻⁵). Conclusions: AI-HOPE-RTK-RAS exemplifies a new class of conversational AI platforms tailored to precision oncology, enabling integrative, real-time analysis of clinically and biologically complex questions. Its ability to uncover both canonical and ancestry-specific patterns in RTK-RAS dysregulation—especially in EOCRC and populations with disproportionate health burdens—underscores its utility in advancing equitable, personalized cancer care. This work demonstrates the translational potential of domain-optimized AI tools to accelerate biomarker discovery, support therapeutic stratification, and democratize access to multi-omic analysis. Full article

This study was conducted using Geographic Information Systems (GISs), Remote Sensing (RS) techniques, and the SLEUTH model based on Cellular Automata (CA) to analyze the spatial and temporal dynamics of urban growth in Sanliurfa Province and to create future projections. The model in question simulates urban sprawl by using Slope, Land Use/Land Cover (LULC), Excluded Areas, urban areas, transportation, and hill shade layers as inputs. In addition, disaster risk areas and public policies that will affect the urbanization of the city were used as input layers. In the study, the spatial pattern of urbanization in Sanliurfa was determined by using Landsat satellite images of six different periods covering the years 1985–2025. The Analytical Hierarchy Process (AHP) method was applied within the scope of Multi-Criteria Decision Analysis (MCDA). Weighting was made for each parameter. Spatial analysis was performed by combining these values with data in raster format. The results show that the SLEUTH model successfully reflects past growth trends when calibrated at different spatial resolutions and can provide reliable predictions for the future. Thus, the proposed model can be used as an effective decision support tool in the evaluation of alternative urbanization scenarios in urban planning. The findings contribute to the sustainability of land management policies. Full article

Everolimus (EVE), an mTOR inhibitor, is widely used in solid organ transplantation (SOT) because of its immunosuppressive properties. Due to its narrow therapeutic window and significant pharmacokinetic variability, therapeutic drug monitoring (TDM) is essential for achieving optimal outcomes. We developed and thoroughly validated a robust LC-MS/MS method to measure EVE levels in venous whole blood (WB) and capillary blood collected using two microsampling devices: Mitra™ (volumetric absorptive microsampling, VAMS) and Capitainer^® (quantitative dried blood spot, qDBS). The validation followed EMA and IATDMCT guidelines, assessing linearity (1.27–64.80 ng/mL for WB and 0.50–60 ng/mL for VAMS/qDBS), as well as selectivity, accuracy, precision, matrix effects, recovery, stability, and incurred sample reanalysis. Clinical validation involved 66 matched samples from 33 adult SOT recipients. The method demonstrated high accuracy and precision across all matrices, with no significant carryover or matrix interference. Statistical analysis using Passing–Bablok regression and Bland–Altman plots showed excellent agreement between the microsampling methods and the venous reference. Hematocrit effects were tested both in laboratory conditions and on clinical samples and were found to be negligible. This study provides the first comprehensive analytical and clinical validation of the Mitra and Capitainer devices for EVE monitoring. The validated LC-MS/MS microsampling method supports decentralized, patient-centred TDM, offering a reliable alternative to conventional blood sampling in transplant care. Full article

In this study, high-energy milled (HEM) samples of natural phosphorites from Estonian deposits were investigated. The activation was performed via planetary mill with Cr-Ni grinders with a diameter of 20 mm. This method is an ecological alternative, since it eliminates the disadvantages of conventional acid methods, namely the release of gaseous and solid technogenic products. The aim of the study is to determine the changes in the structure to follow the solid-state transitions and the isomorphic substitutions in the anionic sub-lattice in the structure of the main mineral apatite in the samples from Estonia, under the influence of HEM activation. It is also interesting to investigate the influence of HEM on structural-phase transformations on the structure of impurity minerals-free calcite/dolomite, pyrite, quartz, as well as to assess their influence on the thermal behavior of the main mineral apatite. The effect of HEM is monitored by using a complex of analytical methods, such as chemical analysis, powder X-ray diffraction (PXRD), wavelength-dispersive X-ray fluorescence (WD-XRF) analysis, and Fourier-transformed infrared (FTIR) analysis. The obtained results prove the correlation in the behavior of the studied samples with regard to their quartz content and bonded or non-bonded carbonate ions. After HEM activation of the raw samples, the following is established: (i) anionic isomorphism with formation of A and A-B type carbonate-apatites and hydroxyl-fluorapatite; (ii) solid-phase synthesis of calcium orthophosphate-CaHPO₄ (monetite) and dicalcium diphosphate-β-Ca₂P₂O₇; (iii) enhanced chemical reactivity by approximately three times by increasing the solubility via HEM activation. The dry milling method used is a suitable approach for solving technological projects to improve the composition and structure of soils, increasing soil fertility by introducing soluble forms of calcium phosphates. It provides a variety of application purposes depending on the composition, impurities, and processing as a soil improver, natural mineral fertilizer, or activator. Full article

The ongoing rise in global electricity demand highlights the need for advanced, efficient, and environmentally responsible energy conversion technologies. This research presents a comprehensive design, modeling, and experimental validation of a tubular permanent magnet linear alternator (PMLA) integrated with a free piston engine system. Linear alternators offer a direct conversion of linear motion to electricity, eliminating the complexity and losses associated with rotary generators and enabling higher efficiency and simplified system architecture. The study combines analytical modeling, finite element simulations, and a sensitivity-based design optimization to guide alternator and engine integration. Two prototype systems, designated as alpha and beta, were developed, modeled, and tested. The beta prototype achieved a maximum electrical output of 550 W at 57% efficiency using natural gas fuel, demonstrating reliable performance at elevated reciprocating frequencies. The design and optimization of specialized flexure springs were essential in achieving stable, high-frequency operation and improved power density. These results validate the effectiveness of the proposed design approach and highlight the scalability and adaptability of PMLA technology for sustainable power generation. Ultimately, this study demonstrates the potential of free piston linear generator systems as efficient, robust, and environmentally friendly alternatives to traditional rotary generators, with applications spanning hybrid electric vehicles, distributed energy systems, and combined heat and power. Full article

This study investigates the application of the Analytic Hierarchy Process (AHP) as a decision-support mechanism for managing complex sustainability issues in industrial settings, specifically within the framework of circular economy principles. Focusing on a case from the brewery sector, developed under the EU ECOFACT initiative, this research evaluates ten distinct configurations for the must cooling process. These alternatives are assessed using environmental, economic, and technical criteria, drawing on data from life cycle assessment (LCA) and life cycle costing (LCC) methodologies. The findings indicate that selecting an optimal scenario involves balancing trade-offs among electricity and water consumption, operational efficiency, and overall environmental impacts. Notably, Scenario 3 emerges as the most balanced option, consistently demonstrating superior performance across the primary evaluation criteria. The use of AHP in this context proves valuable by introducing structure and transparency to a multifaceted decision-making process where quantitative metrics and sustainability objectives intersect. By integrating empirical industrial data with an established multi-criteria decision approach, this study highlights both the practical utility and existing limitations of conventional AHP, particularly its diminished ability to discriminate between alternatives when their scores are closely aligned. These insights suggest that hybrid or advanced AHP methodologies may be necessary to facilitate more nuanced decision-making for circular economy transitions in industrial environments. Full article