Method For Quantification Research Articles

Quantitative BOLD (qBOLD) imaging of oxygen metabolism and blood oxygenation in the human body: A scoping review.

There are many approaches to the quantitative BOLD (qBOLD) technique described in the literature, differing in pulse sequences, MRI parameters and data processing. Thus, in this review, we summarized the acquisition methods, approaches used for oxygenation quantification and clinical populations investigated. Three databases were systematically searched (Medline, Embase, and Web of Science) for published research that used qBOLD methods for quantification of oxygen metabolism. Data extraction and synthesis were performed by one author and reviewed by a second author. A total of 93 relevant papers were identified. Acquisition strategies were summarized, and oxygenation parameters were found to have been investigated in many pathologies such as steno-occlusive diseases, stroke, glioma, and multiple sclerosis disease. A summary of qBOLD approaches for oxygenation measurements and applications could help researchers to identify good practice and provide objective information to inform the development of future consensus recommendations.

A novel RP-HPLC method for the simultaneous quantification of azithromycin and dexamethasone in marketed ophthalmic drops

A straightforward, precise, accurate, specific, and sensitive RP-HPLC technique has been established for the quantification of Azithromycin Dihydrate and Dexamethasone Sodium Phosphate in their commercial formulation. The wavelength maxima for Azithromycin and Dexamethasone were considered to be 215 nm for estimation. In RP-HPLC separations were carried out on a Zorbax SB C18 column (250mm X 4.6mm, 5 μm) and mobile phase consisting of Acetonitrile: Monobasic Potassium Phosphate (KH2PO4) buffer in the proportion of 75:25 v/v and pH of the buffer was adjusted to 5.5 with OPA. The estimation was carried out at 215 nm using UV detector keeping the flow rate of 1.2 ml/min and injection volume of 50 μl. The current method demonstrates good linearity over the range of 20 - 120 μg/ml and 2 - 12 μg/ml for Azithromycin and Dexamethasone respectively. No interference of excipients was found during estimation. The recommended techniques were verified and determined to be specific, accurate, and exact. The approaches were effectively used for the concurrent quantification of both medicines in pharmaceutical formulations, making them suitable for regular quality control examination.

Quantifying late gadolinium enhancement improved sudden cardiac death risk prediction in non-ischemic dilated cardiomyopathy

Abstract Background While previous studies have proved the late gadolinium enhancement (LGE) was associated with poor prognosis in non-ischemic dilated cardiomyopathy (DCM), the optimal method for LGE quantification and the ability of LGE extent in identifying sudden cardiac death (SCD) remain less clarified. Purpose This study sought to compare the reproducibility of LGE quantification methods and explore the asssociation between LGE extent and SCD endpoint in DCM patients. Methods In this prospective study, LGE was quantified by the 2-6 standard deviations (SD) above the remote myocardium and full-wide half-maximum (FWHM) methods. The primary endpoint was SCD and arrythmia endpoint included SCD and aborted SCD. Reproducibility of LGE quantification was measured by Bland-Altman analysis and intra-class correlation coefficients (ICC). Competing risk regression analysis, C-index and area under the curve (AUC) were performed to identify the prognostic value. Results Among the 770 patients, 336 (44%) patients had LGE. FWHM demonstrated the best reproducibility compared with other quantification methods (intraobserver variability: ICC = 0.94, mean bias: -0.43 ± 4.89%; interobserver variability: ICC = 0.90, mean bias: -2.65 ± 6.40%). After a median follow-up of 49 months, SCD occurred in 61 (8%) patients and arrythmia endpoint occurred in 87 (11%) patients. Among all quantification method, LGE extent measured by FWHM showed the highest predictive value of SCD (C index: 0.72) and arrythmia events (C index: 0.71) than other methods. In the competing risk analysis, LGE extent was independently association with SCD (Hazard ratio [HR] 1.05, 95% confidence interval [CI] 1.03 - 1.07, P < 0.001) and arrythmia endpoint (HR 1.05, 95% CI 1.03 - 1.06, P < 0.001). LGE extent >8% showed significantly higher risk of SCD and arrythmia endpoint than those with LGE extent ≤8% (P < 0.001). Incoporating LGE exent and 35% left ventricular ejection fraction (LVEF) significantly improved the SCD (C index: 0.74 vs 0.61, P < 0.001) and arrythmia endpoint (C index: 0.73 vs 0.59, P < 0.001) prediction compared with LVEF. Conclusions FWHM demonstrated best reproducibility and highest SCD prediction ability among LGE quantification methods. Adding LGE extent to LVEF significantly improved the predictive value of SCD and arrythmia endpoint.Figure 1

A 2D echocardiographic method for accurate right ventricular quantification using deep learning

Abstract Background/Introduction Transthoracic two-dimensional echocardiography (2DE) remains the backbone for non-invasive assessment of the right ventricle (RV) size and function. However, calculation of RV end-diastolic (RVEDV), end-systolic volume (RVESV) and ejection fraction (RVEF) cannot be performed using 2DE due to the complex RV shape (1), whereas currently used, respective 2DE indices lack diagnostic accuracy. Deep learning (DL) may be able to assist in developing new 2DE methods for RV quantification. Purpose To develop a novel DL-based 2DE method for quantitative evaluation of RV size and function without geometric assumptions. Methods 50 adult patients underwent 2DE and CMR within 30 days as part of routine cardiac care between 6/2020 – 9/2021 at a medical center. We excluded patients with prior cardiac surgery of the RV, tricuspid or pulmonic valve repair or replacement, complex congenital heart disease, more than small pericardial effusion, cardiac tamponade, atrial fibrillation at the time of either study, severe RV dysfunction or inadequate imaging quality. End-diastolic and end-systolic areas derived from planimetry of 8 2DE RV views, along with patient age and gender, were to used to train and test a DL algorithm, namely the Feature-Tokenizer and Transformer (Figure 1) in order to predict the corresponding, CMR-derived, RVEDV or RVESV, and subsequently calculate RVEF. We used 5-fold cross-validation for training and evaluation. We assessed the relative importance of each 2DE view using gain metric-powered explainability analysis and subsequently performed a sensitivity analysis to identify optimal combinations of views. Variability analysis was performed for a random subcohort of 10 patients. Results Median age was 51 (interquartile range 32-62) and 42% were women. Mean RVEDV, RVESV and RVEF) by CMR were 163±70ml, 82±42ml and 51±8% respectively. Six patients (12%) had RV dilatation and 9 (18%) had RV dysfunction when using published CMR criteria. Explainability analysis showed that the 3 most important views were parasternal long axis (PLAX) (relative feature importance [RFI] = 0.197), 4-chamber (RFI=0.145) and parasternal short axis at the base (PSAX-base) (RFI=0.112). The 3-view combination of PLAX, 4-chamber and PSAX-base achieved high accuracy when compared to CMR (R2=0.964, absolute percentage error [APE]=8.09±12.07% for RV volumes and APE=9.86±10.68% for RVEF). Good (intraclass correlation coefficient [ICC]>0.75) to excellent (ICC>0.90) intra- and interobserver variability was found for these 3 views. Conclusions We propose an innovative, clinically applicable DL-based 2DE method for quantification of RV size and function that requires manual RV planimetry of 3 views, namely 4-chamber, PLAX and PSAX-base (Figure 2). This method may revolutionize 2DE RV assessment. Further studies with largest number of patients and wider range of RV size and function are needed to validate this method.Deep learning architectureGraphical abstract

A bioanalytically validated RP-HPLC method for simultaneous quantification of rivaroxaban, paracetamol, and ceftriaxone in human plasma: a combination used for COVID-19 management

Rivaroxaban is a direct oral anticoagulant medication that has been found to be beneficial for the management of thromboembolic events linked to the Corona virus disease 2019 (COVID-19) pandemic, which has resulted in more than 6 million deaths worldwide. Hence, a sensitive, selective, and green bioanalytically validated method was developed using RP-HPLC coupled with DAD for the simultaneous determination of rivaroxaban in human plasma, and two co-administered drugs, namely, paracetamol, an analgesic, and ceftriaxone, an antibiotic, that are used in the management of COVID-19. An Exsil 100 ODS C18 column (250 × 4.6 mm, 5 μm) was used as the stationary phase, and acetonitrile: water: methanol at a ratio of 60:30:10 (v/v/v) was used in isocratic mode as the mobile phase with a flow rate of 0.7 ml/min. The method was validated over a concentration range of 0.1–10.0 µg/mL for rivaroxaban, and 1.0–15.0 µg/mL for paracetamol and ceftriaxone. The lower limits of detection (LLODs) were found to be 0.03, 0.32, and 0.32 µg/ml for rivaroxaban, paracetamol, and ceftriaxone, respectively. Moreover, the lower limits of quantitation (LLOQs) were found to be 0.1, 0.96, and 0.98 µg/ml. The developed method showed excellent accuracy and precision for the determination of the aforementioned drugs. Four metrics were used to evaluate the greenness of the developed method. The results revealed that the suggested method is green, with values of 81 and 0.6 for the analytical eco-scale and analytical greenness assessment (AGREE), respectively.

Label-free long-term measurements of adipocyte differentiation from patient-driven fibroblasts and quantitative analyses of in situ lipid droplet generation

The visualization and tracking of adipocytes and their lipid droplets (LDs) during differentiation are pivotal in developmental biology and regenerative medicine studies. Traditional staining or labeling methods, however, pose significant challenges due to their labor-intensive sample preparation, potential disruption of intrinsic cellular physiology, and limited observation timeframe. This study introduces a novel method for long-term visualization and quantification of biophysical parameters of LDs in unlabeled adipocytes, utilizing the refractive index (RI) distributions of LDs and cells. We employ low-coherence holotomography (HT) to systematically investigate and quantitatively analyze the 42-day redifferentiation process of fat cells into adipocytes. This technique yields three-dimensional, high-resolution refractive tomograms of adipocytes, enabling precise segmentation of LDs based on their elevated RI values. Subsequent automated analysis quantifies the mean concentration, volume, projected area, and dry mass of individual LDs, revealing a gradual increase corresponding with adipocyte maturation. Our findings demonstrate that HT is a potent tool for non-invasively monitoring live adipocyte differentiation and analyzing LD accumulation. This study, therefore, offers valuable insights into adipogenesis and lipid research, establishing HT and image-based analysis as a promising approach in these fields.

Review of contemporary fluorescence correlation spectroscopy method in diverse solution studies.

Fluorescence correlation spectroscopy (FCS) is a well-known and established non-invasive method for quantification of physical parameters that preside over molecular mechanisms and dynamics. It combines maximum sensitivity and statistical confidence for the analysis of speed, size, and number of fluorescent molecules and interactions with surrounding molecules by time-averaging fluctuation analysis in a well-defined volume element. The narrow compass of this study is to acquaint the basic principle of diffusion and the FCS method in general regarding variable magnitudes and standardization adjustment. In this review, we give a theoretical introduction, examples of experimental applications, and utensils in solution systems with future perspectives.

Quantitative High-Throughput and High-Sensitivity Glycoprofile Analysis of Therapeutic Glycoproteins Using HILIC-FLD and ESI-MS.

Protein glycosylation is recognized as a Critical Quality Attribute for the biological and therapeutic activity of many recombinant proteins. Therefore, glycosylation should be monitored rigorously to ensure the desired quality, safety, and potency of monoclonal antibodies and other therapeutic glycoproteins. However, glycans are highly heterogeneous structures in proteins, and this poses a challenge for glycoprofile analysis. Hydrophilic interaction liquid chromatography with fluorescence detection has been recognized as a standard method for separation and quantification of released N-glycans after conventional 2-aminobenzamide labeling, but the sample preparation procedure is time-consuming with low sensitivity and poor reproducibility. Here we present a streamlined 96-well plate format platform for high-throughput and high-sensitivity glycan profiling. By taking advantage of rapid glycoprotein denaturation, enzymatic deglycosylation, highly sensitive fluorescent derivation, and on-matrix glycan cleanup, the reaction time has been shortened significantly to approximately 10min. A detailed workflow including two-dimensional chromatography fractionation, exoglycosidase sequential digestion, mass spectroscopy glycan mass confirmation, and data interpretation is described. Potential pitfalls and precautions to be taken to ensure data accuracy are also discussed in this chapter.

Assessment of the Choked Flow Model of RELAP5 for Application of Inverse Quantification Methods

In the framework of deterministic safety analysis, best estimate plus uncertainty methodologies can provide a more informative detailed analysis of transients than conservative approaches. However, one important step in the application of such methodologies is derivation of uncertainty of the physical models. Probability density functions of the physical model parameters are obtained by applying inverse uncertainty quantification (IUQ) methods to experimental data. The present work deals with evaluation of the experimental database and assessment of the simulation model, which are required steps prior to the application of IUQ methods. The U.S. Nuclear Regulatory Commission system code RELAP5 has been applied for simulation of three experimental databases on choked/critical flow: Sozzi-Sutherland, Super MobyDick, and Marviken Critical Flow Tests. First, the adequacy of the experimental data to the specific target domain is carried out, to then proceed to calibration of the input model parameters by combining the use of Gaussian Process metamodels and optimization schemes. The assessment of the simulation models is performed by evaluating independently accuracy, precision, and consistency through four statistical indicators, including a novel indicator to evaluate the consistency of the results. The final results indicate that the model is capable of reproducing the selected experimental database and overall average accuracy, precision, and consistency below the 10% threshold and can be used for application of IUQ methods.

Evaluating the IUCN conservation status of Tritaxis kurnoolensis (R.R.V.Raju & Pull.) R.Y.Yu. & Welzen (Euphorbiaceae), an endemic tree species found in the Eastern Ghats region of Andhra Pradesh, India

Tritaxis kurnoolensis, a small tree of the Euphorbiaceae family, is endemic to a valley within the Sullavai Sandstone plateau in close proximity to the Paleru Reservoir (Owk dam). The species is a narrow endemic. No documented sightings of this species have been recorded beyond the type locality since its description in 1994 by Venkataraju & Pullaiah as Dimorphocalyx kurnoolensis from the Nandyal District of Andhra Pradesh. In this study, the authors applied the grid method for quantification and subjected the species to a meticulous analysis aligning with IUCN Red List Criteria. The distribution was found to be restricted due to habitat (valley) fragmentation, reservoir which is arresting seed dispersal, and destruction caused by tunnel construction civil works. The area of occupancy (AOO) at 16 km² and the extent of occurrence (EOO) at 0.474 km², were systematically computed using GeoCAT. The species is assessed here using the Red List methodology for evaluating extinction risk. Based on its AOO, EOO, and population size, it has been classified as Critically Endangered.

A Narrative Review of Chromatographic Bioanalytical Methods for Quantifying Everolimus in Therapeutic Drug Monitoring Applications

Background: Methods for measuring drug levels in the body are crucial for improving therapeutic drug monitoring (TDM) and personalized medicine. In solid-organ transplants, TDM is essential for the management of immunosuppressive drugs to avoid toxicity and organ rejection. Everolimus is a commonly used immunosuppressant with a small range of safe doses; therefore, it is important to adjust the dose according to each patient's needs. Therefore, reliable methods are required to accurately measure everolimus levels. This study aims to conduct a comprehensive and updated narrative review of chromatographic bioanalytical methods for everolimus quantification. Methods: The authors searched for original research articles published between 2013 and 2023 in Scopus and PubMed and found 295 articles after removing duplicates. Based on their titles and summaries, 30 articles were selected for a detailed review and 25 articles were included in the final analysis. Results: Among the 25 studies, 16 used protein precipitation, mainly with methanol, to prepare the samples, 12 used high-performance liquid chromatography, 11 used ultra-performance liquid chromatography, and 2 used both. Almost all the studies (24 of 25) used tandem mass spectrometry for detection, whereas only 1 used ultraviolet. Conclusions: This comprehensive review of bioanalytical methods for measuring everolimus using chromatography is a useful resource for researchers developing bioanalytical methods for TDM applications. Future trends in everolimus measurement include achieving lower detection limits, owing to the trend of reducing drug doses in therapy by improving sample extraction techniques and using more sensitive methods.

Uncertainty quantification of 3D acoustic shape sensitivities with generalized [formula omitted]-order perturbation boundary element methods

This paper presents a novel perburbation-based method for uncertainty quantification of acoustic fields and their shape sensitivities. In this work, the frequencies of impinging acoustic waves are regarded as random variables. Taylor’s series expansions of acoustic boundary integral equations are derived to obtain nth-order derivatives of acoustic state functions with respect to frequencies. Acoustic shape sensitivity is obtained by directly differentiating acoustic boundary integral equation with respect to shape design variables, and then the nth-order derivatives of shape sensitivity with respect to random frequencies are formulated with Taylor’s series expansions. Based on the nth-order perturbation theory, the statistical characteristics of acoustic state functions and their shape sensitivities can be evaluated. Numerical examples are presented to demonstrate the validity and effectiveness of the proposed algorithm.

Measurement Uncertainty and Validation for Quantification of Marijuana Metabolite: (−)-11-nor-9-Carboxy-Δ9-THC in Human Urine by GC-MS/MS

Background: Since the International Olympic Committee (IOC) was established, sports doping control analyses have revealed a high rate of positive cases for cannabinoids. Cannabinoids were banned in all sports where they were used in competition as per the Prohibited List published annually. Further, it was also included in the threshold drug category. Consequently, developing a reliable method for urine Cannabinoids metabolite quantification plays a pivotal role in sports dope testing. Objective: This work aimed to develop and validate a reliable, cost-effective, robust gas chromatography-tandem mass spectrometry method for detecting (−)-11-nor-9-Carboxy-Δ9- THC component in human urine samples, in compliance with ICH and WADA guidelines. Method: The sample preparation was done by enzymatic hydrolysis for deconjugation, further proceeded with solid phase extraction (SPE), liquid-liquid extraction (LLE), and using an XAD2 column, and N-methyl trimethylsilyl trifluoroacetamide (MSTFA) for derivatization. Results: The linearity was obtained in a range of 50–300 ng/mL, and the correlation coefficient was found to be higher than 0.99. Throughout the entire validation study, the difference in Retention Time (RT) for the analyte, including the Internal Standard (IS), was shown to be less than 1.0%. The quantification limit (LOQ) was calculated at a level of 50 ng/mL in human urine samples for the 3 most abundant ion transitions. The detection limit (LOD) was established at 4 ng/mL. Conclusion: The accuracy, precision, linearity, recovery, quantification limit, and selectivity by GC-MS/MS technique were found acceptable and well satisfactory while following the ICH guidelines. The developed method has been proven to be fit for purpose in accordance with the enforced Guidelines of WADA.

An enhanced deep learning method for the quantification of epicardial adipose tissue

Epicardial adipose tissue (EAT) significantly contributes to the progression of cardiovascular diseases (CVDs). However, manually quantifying EAT volume is labor-intensive and susceptible to human error. Although there have been some deep learning-based methods for automatic quantification of EAT, they are mostly uninterpretable and fail to harness the complete anatomical characteristics. In this study, we proposed an enhanced deep learning method designed for EAT quantification on coronary computed tomography angiography (CCTA) scan, which integrated both data-driven method and specific morphological information. A total of 108 patients who underwent routine CCTA examinations were included in this study. They were randomly assigned to training set (n = 60), validation set (n = 8), and test set (n = 40). We quantified and calculated the EAT volume based on the CT attenuation values within the predicted pericardium. The automatic method demonstrated strong agreement with expert manual quantification, yielding a median Dice score coefficients (DSC) of 0.916 (Interquartile Range (IQR): 0.846–0.948) for 2D slices. Meanwhile, the median DSC for the 3D volume was 0.896 (IQR: 0.874–0.908) between these two measures, with an excellent correlation of 0.980 (p < 0.001) for EAT volumes. Additionally, our model’s Bland-Altman analysis revealed a low bias of -2.39 cm³. The incorporation of pericardial anatomical structures into deep learning methods can effectively enhance the automatic quantification of EAT. The promising results demonstrate its potential for clinical application.

ESG risk management in banks – towards its measurement

The concept of sustainable development has been gaining importance and increasing society's awareness of the need to stop climate change, inequality, social exclusion, and inappropriate corporate practices. Banks increasingly integrate ESG objectives into their business activity. However, it is associated with their exposure to a new type of risk – the ESG risk. ESG risk management for banking institutions has now become not only a fashion and trend but an obligation that they have to fulfil. The main aim of the article is to identify ESG risk and methods of quantification, as well as to assess the exposure to ESG risk of commercial banks in Poland. That’s why the paper presents an in-depth literature review in the field of ESG concept and ESG risk in banks. Then, it describes the adopted methodology of the empirical research. The third section covers a presentation of the obtained results, which include the analysis of ESG risk exposure of the largest banks in the world and selected commercial banks in Poland, mainly based on the volume of the carbon footprint they generate and finally, ESG risk ratings for Polish banks. The following research methods were used in the article: literature studies, case study analysis, observation methods and synthesis methods. The empirical research that was conducted allowed the verification of the research hypothesis, stating that commercial banks in Poland are aware of the need to measure and monitor ESG risk increases. The research indicated that some of the banks in Poland are at an advanced stage of ESG risk management, while the rest of them are just starting their activities in this area. Currently, banks' involvement in ESG issues globally is one of the leading market trends. It becomes not only an option but an imperative for institutions wishing to maintain their market position. Therefore, commercial banks in Poland can and should participate in the implementation of sustainable development assumptions in the coming years.

Effect of furosemide on comprehensive renin-angiotensin-aldosterone system activity of Thoroughbred horses.

Furosemide, a commonly used diuretic, activates the renin-angiotensin-aldosterone system (RAAS) in other species. Little is known about RAAS peptide activation in horses. To evaluate equilibrium analysis as a practical method for RAAS quantification in horses and describe the RAAS response to a single dose of furosemide. We hypothesize that furosemide would cause transient increase in RAAS peptides in horses. 14 healthy adult thoroughbreds from a university teaching herd. Horses received either furosemide (1 mg/kg IV) or saline IV in a crossover study design. Protease-inhibited samples were compared with equilibrium analysis samples with Deming regression analysis. Renin-angiotensin-aldosterone system hormones were evaluated at 0, 0.25, 0.5, 4, and 24 hours postadministration, via equilibrium analysis. Values were compared with a mixed effects model. Correlation between protease inhibition and equilibrium analysis was high for angiotensin I peptide (AngI) and angiotensin II peptide (AngII) (r = .92 and .95, respectively). Baseline RAAS peptide concentrations were below the limit of detection except AngII (median, 7.5 [range, 3.5-14.0] pmol/L). Furosemide administration resulted in an increase in AngI (8.0 [0.5-15.5] pmol/L, P = .03), AngII (33.7 [9.6-57.9] pmol/L, P = .0008), angiotensin III peptide (AngIII) (2.9 [0.9-4.9] pmol/L, P = .0005), angiotensin IV peptide (AngIV) (2.0 [0.6-3.4] pmol/L, P = .0005), and angiotensin 1-5 peptide (Ang1-5) (5.6 [1.2-5.9] pmol/L, P = .003) at 4 hours. Differences are reported as difference in the mean (95% confidence interval [CI]). Furosemide produced an increase in hormones associated with both the classical and alternative RAAS pathways. Serum equilibrium analysis is practical for RAAS analysis in horses.

Spectrometric method for simultaneous quantification of nadifloxacin and salicylic acid in a novel topical dosage form

Acne vulgaris is a prevalent skin disorder that affects many individuals. In the search for effective acne therapy, researchers have found that a combination of Nadifloxacin and Salicylic Acid may produce a synergistic effect. To further investigate this, a study was conducted to devise a spectrophotometric method for simultaneously measuring the concentrations of Nadifloxacin and Salicylic Acid in a novel topical formulation. Simultaneous Estimation Method was employed using methanol as the solvent. Nadifloxacin exhibited an absorbance maximum of 291 nm, while Salicylic Acid showed an absorbance maximum of 297 nm in methanol. Linearity experiments were conducted to determine the concentration ranges for both drugs, which were found to be 2–12 ppm for Nadifloxacin and 5–30 ppm for Salicylic Acid. The recovery results of Nadifloxacin ranged from 82 % to 95 %, while those of Salicylic Acid ranged from 97 % to 110 %. These results indicate the accuracy and reliability of the method. This method was further validated in accordance with the guidelines provided by the International Council for Harmonization (ICH) of Technical Requirements for Human Use. The proposed method has demonstrated its applicability for the simultaneous and quantitative assessment of Nadifloxacin and Salicylic Acid in various dosage forms. This development is significant as it provides a reliable and efficient means of measuring the concentrations of these two drugs in acne therapy formulations.

A New LC-MS/MS-Based Method for the Simultaneous Detection of α-Tocopherol and Its Long-Chain Metabolites in Plasma Samples Using Stable Isotope Dilution Analysis

Background: Our study presented a novel LC-MS/MS method for the simultaneous quantification of α-tocopherol (α-TOH) and its phase II metabolites, α-13′-COOH and α-13′-OH, in human serum using deuterium-labeled internal standards (d6-α-TOH, d6-α-13′-COOH, d6-α-13′-OH). Methods: The method addresses the analytical challenge posed by the significantly different concentration ranges of α-TOH (µmol/L) and its metabolites (nmol/L). Previous methods quantified these analytes separately, which caused an increase in workflow complexity. Results: Key features include the synthesis of stable isotope-labeled standards and the use of a pentafluorophenyl-based core-shell chromatography column for baseline separation of both α-TOH and its metabolites. Additionally, solid phase extraction (SPE) with a HybridSPE® material provides a streamlined sample preparation, enhancing analyte recovery and improving sensitivity. By utilizing deuterium-labeled standards, the method compensates for matrix effects and ion suppression. This new approach achieves precise and accurate measurements with limits of detection (LOD) and quantification (LOQ), similar to previous studies. Calibration, accuracy, and precision parameters align well with the existing literature. Conclusions: Our method offers significant advantages in the simultaneous analysis of tocopherol and its metabolites despite concentration differences spanning up to three orders of magnitude. In contrast to earlier studies, which required separate sample preparations and analytical techniques for tocopherol and its metabolites, our approach streamlines this process. The use of a solid-phase extraction procedure allows for parallel sample preparation. This not only enhances efficiency but also significantly accelerates pre-analytical workflows, making the method highly suitable for large-scale studies.

Texture Analysis in Volumetric Imaging for Dentomaxillofacial Radiology: Transforming Diagnostic Approaches and Future Directions

This narrative review explores texture analysis as a valuable technique in dentomaxillofacial diagnosis, providing an advanced method for quantification and characterization of different image modalities. The traditional imaging techniques rely primarily on visual assessment, which may overlook subtle variations in tissue structure. In contrast, texture analysis uses sophisticated algorithms to extract quantitative information from imaging data, thus offering deeper insights into the spatial distribution and relationships of pixel intensities. This process identifies unique “texture signatures”, serving as markers for accurately characterizing tissue changes or pathological processes. The synergy between texture analysis and radiomics allows radiologists to transcend traditional size-based or semantic descriptors, offering a comprehensive understanding of imaging data. This method enhances diagnostic accuracy, particularly for the assessment of oral and maxillofacial pathologies. The integration of texture analysis with radiomics expands the potential for precise tissue characterization by moving beyond the limitations of human eye evaluations. This article reviews the current trends and methodologies in texture analysis within the field of dentomaxillofacial imaging, highlights its practical applications, and discusses future directions for research and dental clinical practice.

Methods for determination of antioxidant capacity of traditional and emergent crops of interest in Mexico: An overview

Reactive oxygen species are produced by aerobic organisms, including humans, because of metabolism. They can oxidise biomolecules and cause degenerative and cardiovascular diseases (diabetes, atherosclerosis, and neurological damage, among others). However, the consumption of different plant products is related to the prevention of reactive oxygen species–mediated damage because they contain various antioxidants that inhibit the oxidation of biomolecules. Some important natural antioxidants are carotenoids, flavonoids, polyphenols, and vitamins. These molecules are found in various crops produced in Mexico, some of which have been cultivated for a long time, while others have emerged in recent years. The study of the antioxidant capacity of these crops has increased over time. Different methods are used to determine this capacity, depending on the type of antioxidants. In this review, we analyse the antioxidant quantification methods of various crops of interest in Mexico (traditional and emergent), as well as their relationship to prevent the oxidation of biomolecules.