Microfluidic paper-based analytical device for measurement of pH using as sensor red cabbage anthocyanins and gum arabic.

The objective of this study was to develop and validate a novel microfluidic paper-based analytical device (µPADpH) for determining the pH levels in foods. Anthocyanins from red cabbage aqueous extract (RCAE) were used as its analytical sensor. Whatman No. 1 filter paper was the most suitable for the device due to its porosity and fiber organization, which allows for maximum color intensity and minimal color heterogeneity of the RCAE in the detection zone of the µPADpH. To ensure the color stability of the RCAE for commercial use of the µPADpH, gum arabic was added. The geometric design of the µPADpH, including the channel length and separation zone diameter, was systematically optimized using colored food. The validation showed that the µPADpH did not differ from the pH meter when analyzing natural foods. However, certain additives in processed foods were found to increase the pH values.

Modular, Scalable, and Customizable LC-HRMS for Exposomics.

In this chapter, we describe a multi-purpose, reversed-phase liquid chromatography-high-resolution mass spectrometry (LC-HRMS) workflow for acquiring high-quality, non-targeted exposomics data utilizing data-dependent acquisition (DDA) combined with the use of toxicant inclusion lists for semi-targeted analysis. In addition, we describe expected retention times for >160 highly diverse xenobiotics in human plasma and serum samples. The method described is intended to serve as a generic LC-HRMS exposomics workflow for research and educational purposes. Moreover, it may be employed as a primer, allowing for further adaptations according to specialized research needs, e.g., by including reference and/or internal standards, by expanding to data-independent acquisition (DIA), or by modifying the list of compounds prioritized in fragmentation experiments (MS2).

Generalisation of the yield stress measurement in three point bending collapse tests: application to 3D printed flax fibre reinforced hydrogels.

This paper describes the extrusion pressure's effect on composite hydrogel inks' filaments subjected to collapse tests. The composite considered in this work consists of an alginate-poloxamer hydrogel reinforced with flax fibres. Increased extrusion pressure resulted in more asymmetrical filaments between the support pillars. Furthermore, the material and printing conditions used in the present study led to the production of curved specimens. These two characteristics implicitly limit the validity of the yield stress equations commonly used in open literature. Therefore, a new system of equations was derived for the case of asymmetrical and curved filaments. A post-processing method was also created to obtain the properties required to evaluate this yield stress. This new equation was then implemented to identify the strength of failed hydrogels without flax fibre reinforcement. A statistical analysis showed this new equation's significance, which yielded statistically higher (i.e., 1.15 times larger) strength values compared to the numbers obtained with the open literature equations. At larger extrusion pressures, longer periods were needed for the material to converge towards its final shape. Larger extrusion pressure values led to lower yield stresses within the composite hydrogel filament: a 5 kPa increase in extrusion pressure lowered the yield stress by 19 %. In comparison, a 15 kPa increase led to a 29 % decrease in the yield stress. Overall this study provides guidelines to standardize collapse tests and analysis comparison between different materials.

Greener analysis of eleven basic drugs in blood and urine using carbowax 20M based biofluid sampler (BFS) device.

For the first time, a novel biofluid sampler (BFS) and sample preparation device is applied for the analysis of 11 basic drugs (i.e., pheniramine, chlorpheniramine, fluoxetine, tramadol, amitriptyline, ketamine, diazepam, chlordiazepoxide, clozapine, chlorpromazine, dothiepin) in biological matrices (i.e., blood and urine). BFS utilizes advanced, highly effective sorbents derived from sol-gel sorbent coating technology onto cellulose fabric substrate, improving sample collection and retention. BFS has the capability to retain a biological sample from 10 to 1000 µL without requiring any dilution or pre-treatment of the sample. The biological samples were pipetted onto the BFS device and dried at room temperature. Subsequently, adsorbed analytes were back-extracted into 1000 µL of methanol without requiring any imposed external diffusion process and then analyzed by gas chromatography-mass spectrometry (GC-MS). A one-factor-at-a-time (OFAT) screening procedure was used to extensively screen and optimize several parameters, including sample volume, elution time, solvent volume, and solvent type. Under the optimal conditions of the study, the method was found to be linear within the range 0.1-10 µg mL-1 for both blood and urine. Quantification limits were established for blood samples within the range of 0.072-0.095 µg mL-1 and for urine samples within the range of 0.050-0.069 µg mL-1. The precisions within and between days were less than 7% and 10%, respectively. The target analytes showed good recoveries utilizing the recommended protocol, with ranges of 45.1%-103.4%. Furthermore, the methodology has been effectively implemented in forensic toxicology case work. Moreover, the green characteristics and applicability of the suggested methodology was evaluated using softwares i.e., AGREE and BAGI.

Comparison of analytical-flow, micro-flow and nano-flow LC-MS/MS for sub-proteome analysis.

The accurate and sensitive analysis of sub-proteomic samples, such as host cell proteins (HCPs) in recombinant products and stem cells in medical devices, is crucial for ensuring product safety and efficacy in the biopharmaceutical industry. However, current analytical techniques, such as conventional analytical-flow LC-MS/MS, face limitations in sensitivity due to the low concentrations of target proteins and the complexity of the sample matrix. In this study, a highly sensitive and repeatable micro-flow LC-MS/MS strategy was developed by replacing analytical-flow tubing with micro-flow tubing on an existing analytical-flow LC-MS system for sub-proteomic sample analysis. Method optimization and evaluation were first conducted with monoclonal antibody (mAb) digestion, focusing on enhancing sensitivity and repeatability. Over 8 days, relative standard deviations (RSDs) for retention time and mass area were less than 5 % and 10 %, respectively. Sensitivity improved by 2.91-4.14 times compared to the analytical-flow LC-MS/MS method. After confirming the reliability of the method, the micro-flow LC-MS/MS method was compared to the nano-flow LC-MS/MS method and the analytical-flow LC-MS/MS method in sub-proteomic sample analysis. For HCPs, the micro-flow LC-MS/MS method demonstrated superior qualitative and much better reproducibility than the nano-flow LC-MS/MS method, with more than 98 % of proteins showing intensity RSD values below 20 %. In the analysis of mesenchymal stem cells (MSCs), the micro-flow method demonstrated good reproducibility and better sensitivity than the analytical-flow method. Taking the analysis of the 20th generation of MSC products as an example, the sample analyzed by micro-flow LC-MS/MS resulted in the identification of 68 % and 8.5 % more peptides and proteins, respectively. Moreover, micro-flow maintained stable system pressure while analyzing umbilical cord stem cells, where nano-flow methods often encounter blockages. This micro-flow LC-MS/MS method is notable for its sensitivity, reproducibility, and straightforward operation, making it highly adaptable for diverse sub-proteomic analyses in biopharmaceutical laboratories.

Diagnostic performance of angiography-derived fractional flow reserve compared to pressure wire-derived fractional flow reserve: Rationale and design of MPFFR pivotal trial.

BACKGROUND: Cardiovascular disease remains the leading cause of death and the use of percutaneous coronary intervention (PCI) is steadily increasing. Current guidelines advocate the use of the fractional flow reserve (FFR) to assess coronary stenosis and treatment strategies; however, invasive FFR has some limitations. Angiography-derived FFR is a potential alternative for calculating FFR from two-dimensional (2D) angiographic images, thereby reducing invasiveness and complications. A novel artificial intelligence (AI)-based angiography-derived FFR, named "MPFFR," offers automated operator-independent hemodynamic calculations; this phase 3 trial aims to validate its diagnostic performance against 2D-quantitative coronary angiography (QCA). METHODS AND ANALYSIS: This pivotal MPFFR trial is a prospective, multicenter, single-blind study. This trial involves patients with coronary artery disease (CAD) from eight cardiovascular centers. Invasive FFR will be performed according to standard guidelines and defined as the reference standard. Angiography-derived FFR will be computed using a proprietary method and 2D-QCA will be performed using validated software. The primary endpoint is the area under the curve for identifying physiologically significant coronary stenosis (FFR ≤0.80), with secondary endpoints including diagnostic accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and correlations between angiography-derived and invasive FFR. This study is designed to demonstrate the superiority of angiography-derived FFR over 2D-QCA and is powered to achieve this with a sample size of 240 patients. Medipixel Inc. supports the trial and is not involved in the data analysis or management.

Whiteness, redness, blueness and greenness profile assessment and design of experiments approach to microwave-aided sensitive and green spectrofluorophotometric determination of baclofen.

As a gamma amino butyric acid-ergic agonist, Baclofen is often prescribed to adults and children for the treatment of severe spasticity that originates in the brain or spinal cord. Even after reviewing the literature extensively, no one has documented a method for estimating baclofen using microwave-assisted stability-indicating spectrofluorimetric techniques, despite the abundance of options for baclofen stability, assay, and bioanalysis. Organic solvents, which are typically necessary for current procedures but may be costly and toxic, have a severe effect on aquatic life and the environment. Using green solvents and 4-chloro-7-nitrobezofuran as a fluorescent probe, this work conducted a stability-indicating spectrofluorimetric estimate of baclofen. Through the use of a design-of-experiments technique, a reliable microwave-aided spectrofluorimetric method was developed, with little solvent consumption and time for sample analysis. Prior to conducting response surface analysis and optimizing important variables and responses, a fractional factorial design was used to screen method variables and responses. A central composite design was then employed for these purposes. This flexible spectrofluorimetric technique was used to assess baclofen concentrations in forced degraded samples and marketed formulations. For baclofen determination, the suggested spectrofluorimetric approach was found to be green, quick, easy to use, economical, and user-friendly.

An analytical case study of the oil well blowout at Baghjan oil field, Assam: A human and environmental perspective.

The study analyses the oil well blowout that took place at the Baghjan oil field in Assam, India, on 27 May 2020. This incident escalated into a massive fire on 9th June that lasted more than 5 months. The tragedy degraded the environment and inflicted substantial problems on the area's inhabitants. The present study employs the analytical case study approach and various data sources to unfold the disaster and its causes, impact, and response. It also examines the local inhabitants and environmental impact and tries to analyze the event comprehensively. The incident resulted from technical malfunctions and human errors, leading to the relocation of the adjacent settlement to refugee camps amidst the global COVID-19 epidemic. However, it is essential to mention that many households received adequate compensation for their damages. The incident has resulted in the contamination of the air, noise, soil, and water, causing significant damage to the fragile ecosystem and its rare species. The research employs the Normalized Difference Vegetation Index to quantify changes in vegetation cover resulting from the blowout, thus showing the extensive damage to the affected region. The incident shed light on legal and regulatory deficiencies alongside a lack of accountability and transparency within the Oil India Limited sector. Despite the numerous proposals for environmental restoration, it appears challenging to revert to the previous state swiftly. The present study reflects the collective and collaborative action to protect and preserve the environment.

Utility, feasibility, and socio-demographic considerations in the diagnosis of bacterial RTI's by GC-IMS breath analysis.

Diagnosis of respiratory tract infections (RTIs), especially in primary care, is typically made on clinical features and in the absence of quick and reliable diagnostic tests. Even in secondary care, where diagnostic microbiology facilities are available, these tests take 24-48 h to provide an indication of the etiology. This multicentre study used a portable gas chromatography-ion mobility spectrometer (GC-IMS) for the diagnosis of bacterial RTIs. Breath samples taken from 570 participants with 149 clinically validated bacterial and 421 non-bacterial RTIs were analyzed to distinguish bacterial from non-bacterial RTIs. Through the integration of a sparse logistic regression model, we identified a moderate diagnostic accuracy of 0.73 (95% CI 0 · 69, 0 · 77) alongside a sensitivity of 0 · 85 (95% CI 0 · 79, 0 · 91) and a specificity of 0 · 55 (95% CI 0 · 50, 0 · 60). The GC-IMS diagnostic device provides a promising outlook in distinguishing bacterial from non-bacterial RTIs and was also favorably viewed by participants.

Decoding the genomic enigma: Approaches to studying extrachromosomal circular DNA.

Extrachromosomal circular DNA (eccDNA), a pervasive yet enigmatic component of the eukaryotic genome, exists autonomously from its chromosomal counterparts. Ubiquitous in eukaryotes, eccDNA plays a critical role in the orchestration of cellular processes and the etiology of diseases, particularly cancers. However, the full scope of its influence on health and disease remains elusive, presenting a rich vein of research yet to be mined. Unraveling the complexities of eccDNA necessitates a distillation of methodologies - from biogenesis to functional analysis - a landscape we overview in this study with precision and clarity. Here, we systematically outline cutting-edge methodologies from high-throughput sequencing and bioinformatics to experimental validations, showcasing the intricate world of eccDNAs. We combed through a treasure trove of auxiliary research resources and analytical tools. Moreover, we chart a course for future inquiry, illuminating the horizon with potential groundbreaking strategies for designing eccDNA research projects and pioneering new methodological frontiers.

Insights into Mechanistic Aspect of Organic Materials for Aluminum-Ion Batteries.

Rechargeable aluminum-ion batteries (AIBs) with organic electrode materials have garnered significant attention due to their excellent safety profile, cost-effectiveness, and eco-friendly nature. This review delves into the intrinsic attributes of organic compounds and their impact on battery performance, mainly focusing on the alteration of ion interactions and charge storage mechanisms at the active sites. The ultimate aim is to propose innovative design approaches for AIBs that overcome the constraints associated with various types of organic materials. The review also discusses the application of advanced analytical tools, providing insights to better understand the electrochemical process of AIBs.

Spectrofluorimetric determination of tapinarof via Zn (II) complexation and assessment of its topical dosage application.

Topical tapinarof is used to treat plaque psoriasis (a skin disease in which red and scaly patches form are appeared on some areas of the body). The goal of the current research is to establish a facile and rapid fluorimetric technique for tapinarof analysis. The approach relied on the reaction between the drug and zinc ion through metal complexation to produce a highly-fluorescent product. The fluorescence was further enhanced by adding sodium dodecyl sulfate, and it was observed at 542 nm following excitation at 497 nm. With a correlation coefficient of 0.9997, the association between emission intensity and tapinarof concentration was linear between 2.0 and 120 ng mL-1. 1.021 ng mL-1 was the quantitation limit while 0.366 ng mL-1 was the detection limit. The buffer type, pH and concentration, type of surfactant and concentration, and finally the diluting solvent were among the reaction conditions that were closely examined and it was found that the optimum conditions were obtained upon employing teorell-stenhagen buffer optimized at pH 6.0, 1.38 × 10-2 M SDS and distilled water as a solvent are the suitable choice. With great precision and reliability, the drug under study was quantified using this method in ointment formulations. The proposed method's level of greenness was assessed using two methodologies: the analytical greenness metric (AGREE) and the Green Analytical Procedure Index (GAPI), with good recovery results ensuring high efficiency of the proposed approach on analysis of ointment without any interference from additives and excipients.

Surface enhanced transmission Raman spectroscopy: Quantitative performances for impurity analysis in complex matrices.

A transmission detection mode was investigated with SERS analyses (SETRS). A comparison between backscattering and transmission detection modes was conducted to demonstrate the feasibility of performing SETRS analyses. The impact of various parameters on the SERS signal intensity such as sample volume, lens collection optic, laser beam size and laser power were then examined. The analytical performances of SETRS were further evaluated through the quantification of an impurity (4-aminophenol) ranging from 3 to 20 µg/mL in a commercial pharmaceutical product using a total error risk-based approach. To account for expected variability of routine analysis, 9 batches of silver nanoparticles suspensions were used and experiments were performed over 5 different days and by 2 operators. Univariate spectral analysis based on a quadratic regression was compared to a multivariate approach using a partial least square regression. The presented results demonstrated that SETRS can be used to determine an impurity in a complex matrix opening new perspectives for quantitative applications.

Copper and nitrogen-doped carbon quantum dots as green nano-probes for fluorimetric determination of delafloxacin; characterization and applications.

BACKGROUND: Carbon quantum dots (CQDs) have gained much interest recently for being efficient probes. Their cost-effectiveness, eco-friendliness, and unique photocatalytic activities made them distinctive alternatives to other luminescent approaches like fluorescent dyes and luminous derivatization. Meanwhile, delafloxacin (DLF) is a recently approved antibacterial medicine. DLF has been authorized for the treatment of soft-tissue and skin infections as well as pneumonia. Therefore, new eco-friendly, cost-effective, and sensitive tools are needed its estimation in different matrices. RESULTS: In the proposed study, green copper and nitrogen carbon dots (Cu-N@CDs) were synthesized from a green source (plum juice with copper sulphate). Cu-N@CQDs were then characterized using multiple tools including X-ray photon spectroscopy (XPS), FTIR and UV-VIS spectroscopy, Zeta potential measurements, High-resolution transmission electron microscopy (HRTEM), and fluorescence spectroscopy. After gradually adding DLF, the developed quantum dots' fluorescence was significantly enhanced within the working range of 0.5-100.0 ng mL-1. The limits of detection and quantification were 0.08 and 0.27 ng mL-1, respectively. The accuracy of the proposed method ranged from 96.00 to 99.12 % in recovery%, when recovered from milk and plasma samples. SIGNIFICANCE: Cu-N@CDs were utilized and validated for selectively determining DLF in several matrices including pharmaceutical forms, human plasma and in milk samples using spectrofluorimetric technique. The bio-analytical method is simple and could be used in content uniformity testing as well as in therapeutic drug monitoring in human plasma.

Decoding stakeholder priorities of safety culture preferences in the oil and gas industry.

Safety culture is a critical determinant of organisational performance, particularly in high-risk industries especially in oil and gas. Understanding stakeholder preferences is essential for developing effective strategies that enhance safety culture. This study utilised the Analytic Hierarchy Process (AHP) to prioritise stakeholder preferences, identifying key elements of safety culture in Malaysia's oil and gas sector. This study employed a structured methodology to evaluate safety culture within the oil and gas industry, focusing on 18 sub-elements across three key domains: psychological, behavioural, and situational factors. A diverse sample of industry experts was recruited using purposeful and snowball sampling to ensure a comprehensive representation of stakeholder views. The AHP framework was applied to analyse the data, utilizing structured questionnaires and multicriteria decision-making techniques to prioritize the identified safety culture elements. The AHP analysis identified distinct priorities among different professional groups within the oil and gas sector. Safety and Health Practitioners emphasized practical elements such as safety rules and management commitment, while academicians prioritized knowledge and training. Management personnel highlighted the importance of safety ownership and communication, whereas policymakers focused on broader, policy-oriented aspects. The findings suggest that safety culture improvement initiatives should be tailored to address the specific needs and priorities of each professional group. A nuanced understanding of stakeholder preferences is crucial for developing comprehensive strategies that integrate observable behaviours, situational conditions, and psychological factors, ultimately fostering a robust safety culture in the oil and gas industry.

The forecasting of surface displacement for tunnel slopes utilizing the WD-IPSO-GRU model.

To quickly assess slope stability based on field displacement monitoring data, this paper constructs a hybrid optimization model that predicts surface displacement during tunnel excavation in base-overburden slopes. The model combines Wavelet Decomposition (WD) with a Gated Recurrent Unit (GRU), and the GRU's hyperparameters are optimized using an Improved Particle Swarm Optimization algorithm (IPSO). The specific steps are as follows: First, the Wavelet Decomposition (WD) technique is applied to decompose the raw displacement data, extracting features at different time-frequency scales. Next, the Dropout technique is incorporated into the GRU model to prevent overfitting. Additionally, nonlinear inertia weight ω improved cognitive factor c1, and social factor c2 are introduced. The PSO algorithm is improved by integrating crossover and mutation concepts from genetic algorithms. Finally, the IPSO is used to optimize the number of neural units hN, HN, LN and dropout rates D1 and D2 in the GRU network architecture. After constructing the WD-IPSO-GRU model, a comprehensive comparison is made with various swarm intelligence algorithms and state-of-the-art models. The experimental results demonstrate that the WD-IPSO-GRU model significantly improves the prediction accuracy of surface displacement in slopes during tunnel excavation. Compared to directly using raw data for prediction, the introduction of the WD preprocessing technique improved the prediction accuracy at measurement points 01 and 02 by 28% and 45.9%, respectively. Additionally, with the model optimized by IPSO, the prediction accuracy at measurement points 01 and 02 increased by 76% and 56.7%, respectively. The WD-IPSO-GRU model effectively addresses the challenges of extracting features from univariate displacement time-series data and determining the parameters of the GRU network. It improves the prediction accuracy of surface displacement in base-overburden type slopes and demonstrates excellent generalization ability and reliability. The research results validate the potential application of the model in geotechnical engineering and provide strong support for assessing slope stability during tunnel excavation.

Applicability of metabolomics to improve sustainable grapevine production.

Metabolites represent the end product of gene expression, protein interaction and other regulatory mechanisms. The metabolome reflects a biological system's response to genetic and environmental changes, providing a more accurate description of plants' phenotype than the transcriptome or the proteome. Grapevine (Vitis vinifera L.), established for the production of wine grapes, table grapes, and raisins, holds immense agronomical and economic significance not only in the Mediterranean region but worldwide. As all plants, grapevines face the adverse impact of biotic and abiotic stresses that negatively affect multiple stages of grape and wine industry, including plant and berry development pre- and post-harvest, fresh grapes processing and consequently wine quality. In the present review we highlight the applicability of metabolome analysis in the understanding of the mechanisms involved in grapevine response and acclimatization upon the main biotic and abiotic constrains. The metabolome of induced morphogenic processes such as adventitious rooting and somatic embryogenesis is also explored, as it adds knowledge on the physiological and molecular phenomena occurring in the explants used, and on the successfully propagation of grapevines with desired traits. Finally, the microbiome-induced metabolites in grapevine are discussed in view of beneficial applications derived from the plant symbioses.

Analytical performance evaluation of a new integrated clinical chemistry and immunoassay analyzer.

Background: Clinical laboratories perform a wide range of tests that are used by healthcare professionals to guide medical decision making. Use of automated analyzers in the clinical laboratory can improve patient care by not only reducing the turn-around-time (TAT) of results but also improving accuracy of the reported results by reducing human error. The aim of this study was to evaluate the performance characteristics of a new automated laboratory instrument, the Atellica® CI Analyzer, Model 1900, over a 3-month period in a European laboratory setting. Methods: Analytical performance of 17 analytes (13 chemistry and four immunochemistry) was assessed by evaluating repeatability and within-laboratory precision using anonymized remnant serum samples. Method comparison studies were performed on the Atellica CI Analyzer and the Roche cobas® 6000. Results: Excellent precision was observed with coefficients of variation (CVs) less than 2 % for repeatability and less than 3 % within-laboratory imprecision for most analytes. Comparison of select assays with the cobas 6000 system resulted in correlation coefficients ranging from 0.980 to 1.000. Conclusion: This is the first reported evaluation of the Atellica CI Analyzer in a clinical laboratory setting. The strong analytical performance of the Atellica CI Analyzer demonstrates that this instrument is suitable for routine clinical use.

Pipette-tip kapok fiber-based solid-phase extraction/in-situ derivatization for the rapid and green analysis of furfural compounds.

Furfural compounds, including 5-hydroxymethylfurfural, furfural, and 5-methylfurfural, are common in foods and pose health risks. This study presents a pipette-tip solid-phase extraction with in-situ derivatization (PT-KF-SPE/ISD) method for rapid analysis of furfural compounds in various food matrices. Utilizing natural kapok fiber as an efficient adsorbent, this method integrates extraction and derivatization into a single step via a simple pull-push operation. Derivatization with 2,4-dinitrophenylhydrazine increases the hydrophobicity and ultraviolet absorption of furfural compounds, enabling sensitive liquid chromatography-ultraviolet detection. The method shows good linearity, sensitivity, and reproducibility, with limits of detection in ranges of 3.9-6.0 ng/mL. Real sample analysis confirms its applicability in detecting furfural compounds in beverages and herbal products, offering a reliable and eco-friendly solution for food safety and quality control. Five greenness assessment metrics demonstrate the method's excellent environmental friendliness. This approach highlights the advantages of combining natural adsorbents with in-situ derivatization for efficient food analysis.