Validity Of Method Research Articles

An innovative microplastic extraction technique: the switchable calcium chloride density separation column tested for biodegradable polymers, polyethylene, and polyamide

Extracting microplastics from complex matrices poses challenges due to the potential impact of harsh chemical treatments on microplastic properties. For fate and hazard assessment reliable techniques are needed to not only quantify the particle number but also to assess the physicochemical properties of environmental microplastics with minimum changes induced by extraction. Here we present the method development for an innovative and non-destructive extraction protocol based on a switchable calcium chloride density separation column. In contrast to commonly reported extraction protocols, the presented technique is suitable for targeted microplastic property analysis (e.g., surface chemistry and texture) by keeping chemical treatments (such as oxidation and enzymatic digestion) to a minimum. By adjusting the temperature we can control the aggregate state of the highly concentrated salt solution, allowing to separate the microplastics from matrix by cutting of purified, solidified samples. Harsh chemical treatments are avoided, as well as obstruction of microplastic extraction by adsorption to matrix components when passing the tap at the bottom of traditional density separation funnels.The use of microplastics that were prelabeled with a fluorescence dye helped to solve difficulties observed during method development by visual inspection before measurement of extraction efficiency: We spiked a blank compost with low-density polyethylene (LDPE) and polyamide (PA). Additionally, UV aged LDPE was used to demonstrate applicability to more hydrophilic, more environmentally relevant microplastics. The obtained initial results show high recovery of both unaged and aged LDPE over 97 wt.-% and an efficient compost removal but a lower and less robust recovery (between 68 and 18 wt.-%) for PA particles that are more challenging to extract due to an unfortunate synergistic combination of smaller particle size and higher density. Method adaptation to other microplastic types may still be necessary. In short:A low-cost and simple approach without oxidation to extract (pre-aged) microplastics from compostMethod development by visual observation using fluorescent labelled microplastics and method validation by spike-recovery tests

The Use of Islamic Attribute in Food Product Marketing: Expert Views

The vast number of Muslim consumers in Malaysia, which accounts for 63.5% of the total Malaysian population, offers a vast market segment to food producers—the food producers employ various marketing strategies to compete in the market. Among the strategies employed is the use of Islamic attributes in marketing activities. Food product marketers used Islamic attributes such as Muslim names, pictures, emblems, Quranic verses, and Hadith in their marketing campaigns. The free use of the Islamic attributes has drawn attention to knowing the Islamic perspective of the use. Through in-depth interviews, this research paper aimed to reveal the views of 7 Shariah experts in a rich and contextualized account of using Islamic attributes in food product marketing. The experts were selected through purposive and snowball sampling methods. Thematic analysis was used to analyze the data, which resulted in the emergence of six themes in this study. These themes include (1) protection of Islamic honor and dignity, (2) prohibition of using Islam for personal gain, (3) prohibition of unjust practices, (4) prohibition of superstitious or syirik acts, (5) promotion of good business practices, and (6) promotion of a healthy diet, revealing the Islamic perspective on its use. This study contributes knowledge to Islamic marketing and the rulings on using Islamic attributes according to the Shariah principle. This research sheds light on the ethical implications of using Islamic attributes in scholarly and marketing domains. Further, this research explores the triangulation method of data analysis and validity via Shariah and socio-research.

Validation of oscillometric ratio and maximum gradient methods for non-invasive blood pressure measurement with intra-arterial blood pressure measurements as reference.

Most non-invasive blood pressure (BP) measurements are carried out using instruments which implement either the Ratio or the Maximum Gradient oscillometric method, mostly during cuff deflation, but more rarely during cuff inflation. Yet, there is little published literature on the relative advantages and accuracy of these two methods. In this study of 40 lightly sedated individuals aged 64.1 ± 9.6 years, we evaluate and compare the performance of the oscillometric ratio (K) and gradient (Grad) methods for the non-invasive estimation of mean pressure, SBP and DBP with reference to invasive intra-arterial values. There was no significant difference between intra-arterial estimates of mean pressure made via Korotkoff sounds (MP-OWE) or the gradient method (MP-Grad). However, 17.7% of MP-OWE and 15% of MP-Grad were in error by more than 10 mmHg. SBP-K and SBP-Grad underestimated SBP by 14 and 18 mmHg, whilst accurately estimating DBP with mean errors of 0.4 ± 5.0 and 1.7 ± 6.1 mmHg, respectively. Relative to the reference standard SBP-K, SBP-Grad and DBP-Grad were estimated with a mean error of -4.5 ± 6.6 and 1.4 ± 5.6 mmHg, respectively, noting that using the full range of recommended ratios introduces errors of 12 and 7 mmHg in SBP and DBP, respectively. We also show that it is possible to find ratios which minimize the root mean square error (RMSE) and the mean error for any particular individual cohort. We developed linear models for estimating SBP and SBP-K from a range of demographic and non-invasive OWE variables with resulting mean errors of 0.15 ± 5.6 and 0.3 ± 5.7 mmHg, acceptable according to the Universal standard.

Three-phase model of SCIG-based variable speed wind turbine for unbalanced DSLF analysis

Steady state performances of the electric power distribution system are normally assessed or evaluated based on load flow analysis. To properly carry out the analysis, a valid steady state load flow model of each distribution system component, including the wind power plant (WPP), needs to be developed. The present paper proposes a method for modeling and integrating squirrel cage induction generator (SCIG)-based variable speed WPP into a three-phase unbalanced distribution system load flow (DSLF) analysis. The proposed method is based on a single-phase T-circuit model of fixed speed WPP, which has successfully been applied to balanced electric power systems. In the present work, the single-phase T-circuit model is extended and modified to be used in steady state load flow analysis of three-phase unbalanced distribution systems embedded with SCIG-based variable speed WPP. Results of the case studies confirm the validity of the proposed method.

Quality-by-design optimized RP-HPLC approach for the therapeutic drug monitoring of glibenclamide and fluoxetine in human plasma

Glibenclamide (GLB) and fluoxetine (FLX) were reported to have a potential drug-drug interaction when clinically co-administered. FLX is an inhibitor of CYP2C9 (the enzyme responsible for the metabolism of GLB), thus resulting in increased serum levels of GLB followed by severe hypoglycemia. Therefore, a sensitive, simple, and selective HPLC method is urgently needed for their simultaneous determination in plasma to be utilized for monitoring their therapeutic blood concentration levels. The current study introduces the first RP-HPLC approach for the simultaneous estimation of this binary mixture in less than 7 min. Adopting a quality-by-design (QbD) approach allowed for the designed approach to be optimized. Using a two-level full factorial design (25), the effects of various variables on the chromatographic responses were investigated and optimized. Hypersil BDS C18 column was used for the achievement of the optimum chromatographic separation at 19.9 °C using acetonitrile: sodium dihydrogen phosphate buffer (7.5 mM; pH 4, 60:40 % v/v) as a mobile phase, pumped isocratically at a flow rate of 1.036 mL/min. An injection volume of 30.0 μL was used for the binary mixture with UV detection at 230 nm. FLX and GLB calibration curves revealed an excellent linearity over the ranges of 0.025–10.00 and 0.02–10.00 µg/mL with limits of quantitation of 0.018 and 0.02 µg/mL, respectively. Due to the high sensitivity and selectivity, the method was successfully applied to the assay of the two drugs in spiked human plasma samples with reasonable % recoveries (92.70–108.50 %), indicating good bioanalytical applicability. Therefore, this study could be applied for the therapeutic drug monitoring of GLB and FLX in human plasma to control their potential drug-drug interaction. The suggested approach was also applied to estimate the investigated drugs in their dosage forms with reasonable % recoveries (96.80–102.80 %) and small % RSD values (less than 2 %). The method's excellent greenness was evaluated using three metric tools, including Analytical Eco-Scale, Green Analytical Procedure Index (GAPI), and Analytical Greenness (AGREE). Validation of the proposed method was performed according to ICH and US FDA guidelines.

Bioanalytical method development and validation for the quantification of raloxifene hydrochloride from mice plasma by RP-HPLC

Raloxifene hydrochloride (RLX) belongs to the Selective estrogen receptor modulator (SERM) class of drugs, exhibiting diverse affinity to estrogen receptors. The drug is known for its anti-cancer and anti-osteoporosis activity. The current study employs a Reverse Phase High-Performance Liquid Chromatography (RP-HPLC) method that is sensitive and time-efficient for quantitative evaluation of RLX from mice plasma, using tamoxifen citrate as an internal standard (IS). The protein precipitation technique was used to extract the RLX and IS. RLX was separated using a C8 column with an isocratic elution of a mobile phase consisting of acetonitrile and Milli-Q water (pH 3) at a 1 mL/min flow rate. The ultraviolet (UV) detection of the analyte and IS were carried out at 287 nm. The linearity plot was constructed in the range of 100–3200 ng/mL with a correlation coefficient of r2 ≥ 0.9996. The inter-day and intra-day accuracy and precision were found to be within acceptable limits. Stability studies revealed that the analyte remained stable. The validated RP-HPLC method was successfully applied to quantify RLX after oral administration in mice, and the pharmacokinetic (PK) parameters were established. The present RP-HPLC method could be a beneficial tool for the fast and reliable estimation of future PK interactions, PK analysis of formulations, and therapeutic drug monitoring.

A study on metrological cross-validation of hydrogen refueling stations using a hybrid metrology evaluation system

Hydrogen refueling stations play a pivotal role in advancing hydrogen fuel cell vehicles. Ensuring the accuracy and reliability of these stations is crucial for their safe and efficient operation. This study proposes a hybrid metrology evaluation system for the comprehensive cross-validation of hydrogen refueling stations. The system combines experimental measurements with computational models to thoroughly assess the stations' performance.The main objectives of this study are to evaluate the precision, accuracy, and reliability of hydrogen refueling stations and to identify potential uncertainties or sources of error in measurements. Six refueling experiments were conducted, varying the refueling pressure from 476bar to 735bar and the refueling rate from 0.601486kg/min to 0.702694kg/min. The maximum refueling capacity was determined to be approximately 6.3kg, based on the specifications of the NEXO vehicle.Throughout the experiments, data on critical parameters such as pressure, weight, and flow rate were collected. These data were meticulously analyzed and compared with expected values derived from computational models. The results convincingly demonstrate that the hybrid metrology evaluation system offers a robust and precise evaluation of hydrogen refueling stations. The system adeptly identifies discrepancies between experimental measurements and computational models, facilitating the correction of potential measurement errors.This study contributes significantly to the enhancement of metrological cross-validation techniques for hydrogen refueling stations, ensuring their precision and dependability. The study findings can inform the development of standardized metrological protocols and guidelines for the certification and calibration of hydrogen refueling stations. By establishing accurate and dependable metrological validation methods, the adoption of hydrogen fuel cell vehicles can be expedited, promoting a sustainable and environmentally friendly transportation system.

Determination of vancomycin and meropenem in serum and synovial fluid of patients with prosthetic joint infections using UPLC-MS/MS.

Numerous studies have suggested that intra-articular administration of antibiotics following primary revision surgery may be one of the methods for treating prosthetic joint infection (PJI). Vancomycin and meropenem are the two most commonly used antibiotics for local application. Determining the concentrations of vancomycin and meropenem in the serum and synovial fluid of patients with PJI plays a significant role in further optimizing local medication schemes and effectively eradicating biofilm infections. This study aimed to establish a rapid, sensitive, and accurate ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method for determining the concentrations of vancomycin and meropenem in human serum and synovial fluid. Serum samples were processed using acetonitrile precipitation of proteins and dichloromethane extraction, while synovial fluid samples were diluted before analysis. Chromatographic separation was achieved in 6min on a Waters Acquity UPLC BEH C18 column, with the mobile phase consisting of 0.1% formic acid in water (solvent A) and acetonitrile (solvent B). Quantification was carried out using a Waters XEVO TQD triple quadrupole mass spectrometer with an electrospray ionization (ESI) source in positive ion mode. The multiple reaction monitoring (MRM) mode was employed to detect the following quantifier ion transitions: 717.95-99.97 (norvancomycin), 725.90-100.04 (vancomycin), 384.16-67.99 (meropenem). The method validation conformed to the guidelines of the FDA and the Chinese Pharmacopoeia. The method demonstrated good linearity within the range of 0.5-50 μg/ml for serum and 0.5-100 μg/ml for synovial fluid. Selectivity, intra-day and inter-day precision and accuracy, extraction recovery, matrix effect, and stability validation results all met the required standards. This method has been successfully applied in the pharmacokinetic/pharmacodynamic (PK/PD) studies of patients with PJI.

Analytical method development and validation for the simultaneous estimation of montelukast and Acebrophylline by RP- HPLC method

High performance liquid chromatography is at present one of the most sophisticated tool of the analysis. The estimation of Montelukast and Acebrophylline was done by RP-HPLC. The Phosphate buffer was pH 3.0 and the mobile phase was optimized with consists of Methanol: Phosphate buffer mixed in the ratio of 70:30 % v/ v. Inertsil C18 column C18 (4.6 x 150mm, 5mm) or equivalent chemically bonded to porous silica particles was used as stationary phase. The detection was carried out using UV detector at 260 nm. The solutions were chromatographed at a constant flow rate of 0.8 ml/min. the linearity range of Montelukast and Acebrophylline were found to be from 100-500 mg/ml of Montelukast and 1-5mg/ml of Acebrophylline . Linear regression coefficient was not more than 0.999.The values of % RSD are less than 2% indicating accuracy and precision of the method. The percentage recovery varies from 98-102% of Montelukast and acebrophylline. LOD and LOQ were found to be within limit. The results obtained on the validation parameters met ICH and USP requirements .it inferred the method found to be simple, accurate, precise and linear. The method was found to be having suitable application in routine laboratory analysis with high degree of accuracy and precision.

Non-invasive Scores and Serum Biomarkers for Fatty Liver in the Era of Metabolic Dysfunction-associated Steatotic Liver Disease (MASLD): A Comprehensive Review From NAFLD to MAFLD and MASLD.

The prevalence of non-alcoholic fatty liver disease (NAFLD) is rapidly increasing worldwide, making it the leading cause of liver related morbidity and mortality. Currently, liver biopsy is the gold standard for assessing individuals with steatohepatitis and fibrosis. However, its invasiveness, sampling variability, and impracticality for large-scale screening has driven the search for non-invasive methods for early diagnosis and staging. In this review, we comprehensively summarise the evidence on the diagnostic performance and limitations of existing non-invasive serum biomarkers and scores in the diagnosis and evaluation of steatosis, steatohepatitis, and fibrosis. Several non-invasive serum biomarkers and scores have been developed over the last decade, although none has successfully been able to replace liver biopsy. The introduction of new NAFLD terminology, namely metabolic dysfunction-associated fatty liver disease (MAFLD) and more recently metabolic dysfunction-associated steatotic liver disease (MASLD), has initiated a debate on the interchangeability of these terminologies. Indeed, there is a need for more research on the variability of the performance of non-invasive serum biomarkers and scores across the diagnostic entities of NAFLD, MAFLD and MASLD. There remains a significant need for finding valid and reliable non-invasive methods for early diagnosis and assessment of steatohepatitis and fibrosis to facilitate prompt risk stratification and management to prevent disease progression and complications. Further exploration of the landscape of MASLD under the newly defined disease subtypes is warranted, with the need for more robust evidence to support the use of commonly used serum scores against the new MASLD criteria and validation of previously developed scores.

Digital phenotyping data and anomaly detection methods to assess changes in mood and anxiety symptoms across a transdiagnostic clinical sample.

Clinical assessment of mood and anxiety change often relies on clinical assessment or self-reported scales. Using smartphone digital phenotyping data and resulting markers of behavior (e.g., sleep) to augment clinical symptom scores offers a scalable and potentially more valid method to understand changes in patients' state. This paper explores the potential of using a combination of active and passive sensors in the context of smartphone-based digital phenotyping to assess mood and anxiety changes in two distinct cohorts of patients to assess the preliminary reliability and validity of this digital phenotyping method. Participants from two different cohorts, each n = 76, one with diagnoses of depression/anxiety and the other schizophrenia, utilized mindLAMP to collect active data (e.g., surveys on mood/anxiety), along with passive data consisting of smartphone digital phenotyping data (geolocation, accelerometer, and screen state) for at least 1 month. Using anomaly detection algorithms, we assessed if statistical anomalies in the combination of active and passive data could predict changes in mood/anxiety scores as measured via smartphone surveys. The anomaly detection model was reliably able to predict symptom change of 4 points or greater for depression as measured by the PHQ-9 and anxiety as measured for the GAD-8 for both patient populations, with an area under the ROC curve of 0.65 and 0.80 for each respectively. For both PHQ-9 and GAD-7, these AUCs were maintained when predicting significant symptom change at least 7 days in advance. Active data alone predicted around 52% and 75% of the symptom variability for the depression/anxiety and schizophrenia populations respectively. These results indicate the feasibility of anomaly detection for predicting symptom change in transdiagnostic cohorts. These results across different patient groups, different countries, and different sites (India and the US) suggest anomaly detection of smartphone digital phenotyping data may offer a reliable and valid approach to predicting symptom change. Future work should emphasize prospective application of these statistical methods.

Identification of youth at clinical high-risk for psychosis: A community-based study from India.

A two-stage process, wherein self-report screening precedes the structured interview, is suggested for identifying individuals at clinical high-risk for psychosis (CHR-P) in community samples. Aim of this study was to screen a community youth sample from India for CHR-P using the two-stage method. Specific objectives were to assess concordant validity of the self-report measure and predictive validity of the two-stage method. Based on probability sampling, 2025 youth aged 15-24 years were recruited from one rural and one urban area of Telangana, a Telugu-speaking state in India. Telugu version of the PRIME Screen-Revised (PS-R) and structured interview for psychosis-risk syndromes (SIPS) were used. CHR-P positive and negative cohorts were followed-up for transition to psychosis at 3-monthly intervals. One hundred ten individuals screened positive on PS-R. SIPS conducted on 67 out of 110 individuals confirmed 62 (92.54%) to be CHR-P positive. PS-R showed 98.41% sensitivity and 90.74% specificity. Among CHR-P positive, three participants transitioned to psychosis in 15 months. The hazard ratio for psychosis transition was 11.4. Screening accuracy of PS-R in the community youth sample in Telangana is optimum. The hazard ratio for psychosis transition in the community identified CHR-P indicates good predictive validity for the two-stage method.

Chemometric-based drug discovery approaches from natural origins using hyphenated chromatographic techniques.

Isolation and characterization of bioactive components from complex matrices of marine or terrestrial biological origins are the most challenging issues for natural product chemists. Biochemometric is a new potential scope in natural product analytical science, and it is a methodology to find the compound's correlation to their bioactivity with the help of hyphenated chromatographic techniques and chemometric tools. The present review aims to evaluate the application of chemometric tools coupled to chromatographic techniques for drug discovery from natural resources. The searching keywords "biochemometric," "chemometric," "chromatography," "natural products bioassay," and "bioassay" were selected to search the published articles between 2010-2023 using different search engines including "Pubmed", "Web of Science," "ScienceDirect," and "Google scholar." An initial stage in natural product analysis is applying the chromatographic hyphenated techniques in conjunction with biochemometric approaches. Among the applied chromatographic techniques, liquid chromatography (LC) techniques, have taken up more than half (53%) and also, mass spectroscopy (MS)-based chromatographic techniques such as LC-MS are the most widely used techniques applied in combination with chemometric methods for natural products bioassay. Considering the complexity of dataset achieved from chromatographic hyphenated techniques, chemometric tools have been increasingly employed for phytochemical studies in the context of determining botanicals geographical origin, quality control, and detection of bioactive compounds. Biochemometric application is expected to be further improved with advancing in data acquisition methods, new efficient preprocessing, model validation and variable selection methods which would guarantee that the applied model to have good prediction ability in compound relation to its bioactivity.

Prussian blue nanocubes with peroxidase-like activity for polyphenol detection in commercial beverages.

The present study describes an efficient method for the determination of polyphenol content in beverages based on a composite material of graphene oxide decorated with Prussian blue nanocubes (rGO/PBNCs). In this method, rGO/PBNCs act as a nanoenzyme with peroxidase-like catalytic activity and produce a colorimetric product in the presence of hydrogen peroxide and tetramethylbenzidine (TMB). To verify the effectiveness of the method, we used two model standards for antioxidants: gallic acid (GA) and tannic acid (TA). The method validation included a comparison of the performance of a natural enzyme and an artificial one (rGO/PBNCs) and two polyphenols in the analysis of commercial beverage samples. After optimization, a pH of 4, ambient temperature (22 °C), a reaction time of 2 minutes and an rGO/PBNCs concentration of 0.01 μg mL-1 were found to be the most favorable conditions. The detection limits obtained were 5.6 μmol L-1 for GA and 1.5 μmol L-1 for TA. Overall, rGO/PBNCs offer advantages over natural enzymes in terms of stability, versatility, scalability and durability, making them attractive candidates for a wide range of catalytic and sensory applications.

Development and validation of paper-based strip method for the detection of formalin in milk

Development and validation of paper-based strip method for the detection of formalin in milk

Multi-scale population analysis unit construction method considering scene feature variability and long/short-term patterns in spatiotemporal population activities

ABSTRACT Differences in the spatial scale and component elements of urban scenes affect the analysis of spatiotemporal changes in population distribution (PD) patterns. Fixed scales and geometric forms constrained previous analyses of PD and spatiotemporal changes, which neglected the realistic characteristics of urban scenarios. These limitations hinder the ability to capture the diversity and spatiotemporal representation of PD patterns across multiple spatial scales. This study developed a multi-spatial scale population analysis unit (PAU) construction method considering the scenario heterogeneity and long/short-term patterns of spatiotemporal population changes (PC). Initially, we decompose the multi-scale changes in population time series patterns and their relationships with scene features along the temporal dimension to analyze the primary and secondary factors. Starting from the temporal characteristics of the PD and PC, we established a validation and correction method for the factors. Finally, combined with a multi-feature clustering method, a multi-scale PAU construction method driven by scene feature factors is proposed. Experiments were conducted at different spatial scales in both routine and emergent scenarios. The results indicated that this method can help to obtain more homogeneous analysis regions and enhance the stability and phase pattern representations of changes in PDs, thereby improving the interpretability of analytical results.

The SPECTRAL Perfusion Arm Clamping dAtaset (SPECTRALPACA) for video-rate functional imaging of the skin

Spectral imaging has the potential to become a key technique in interventional medicine as it unveils much richer optical information compared to conventional RBG (red, green, and blue)-based imaging. Thus allowing for high-resolution functional tissue analysis in real time. Its higher information density particularly shows promise for the development of powerful perfusion monitoring methods for clinical use. However, even though in vivo validation of such methods is crucial for their clinical translation, the biomedical field suffers from a lack of publicly available datasets for this purpose. Closing this gap, we generated the SPECTRAL Perfusion Arm Clamping dAtaset (SPECTRALPACA). It comprises ten spectral videos (∼20 Hz, approx. 20,000 frames each) systematically recorded of the hands of ten healthy human participants in different functional states. We paired each spectral video with concisely tracked regions of interest, and corresponding diffuse reflectance measurements recorded with a spectrometer. Providing the first openly accessible in human spectral video dataset for perfusion monitoring, our work facilitates the development and validation of new functional imaging methods.

Klasterisasi Jumlah Penduduk Provinsi Jawa Timur Tahun 2021-2023 Menggunakan Algoritma K-Means

Understanding the population data of a region is crucial for policy development and strategic planning. East Java Province, the second-largest province in Indonesia, has undergone significant population growth from 2021 to 2023. Uneven growth poses challenges in resource and infrastructure management. The K-Means algorithm clusters population data into several groups based on specific characteristics. The Elbow method is used to determine the optimal number of clusters, ensuring the accuracy of the analysis. This research aims to analyze and cluster the population distribution in each city in East Java Province, providing a more detailed and accurate depiction. The research findings reveal three significant clusters. Cluster 0 includes 21 towns, Cluster 1 comprises 4, and Cluster 2 encompasses 13. These findings have important implications for targeted development policy formulation at the city level in East Java Province. Additionally, this study contributes to the development of demographic analysis and population management, using valid methods and consistent results between RapidMiner and manual calculations. In conclusion, this research provides a solid foundation for more effective development policy formulation in East Java Province, offering essential information for sustainable population management.

Simultaneous quantification of terpenes and cannabinoids by reversed-phase LC-APCI-MS/MS in Cannabis sativa L. samples combined with a subsequent chemometric analysis.

Cannabis sativa L. has been the most discussed medicinal plant in recent years. In particular, the dynamic shift from a formerly illicit and tightly controlled substance to a plant recognized for both medicinal and recreational purposes has brought C. sativa into the global spotlight. Due to the ongoing international legalization processes, fast and convenient analytical methods for the quality control of C. sativa flowers for medicinal and recreational purposes are of tremendous interest. In this study, we report the development and validation of a liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based method applying atmospheric pressure chemical ionization (APCI) to fully quantify 16 terpenes and 7 cannabinoids including their acidic forms by a single chromatographic method. The method presented here is unique and simple, as it eliminates the need for derivatization reactions and includes the unconventional analysis of volatile compounds by liquid chromatography. Samples were prepared by a simple and fast ethanolic extraction. Separation was accomplished within 25min on a reversed-phase C18 column. Method validation was conducted according to international guidelines regarding selectivity, accuracy, precision, robustness, and linearity. Detection was done in multiple reaction monitoring, which allowed the simultaneous quantification of co-eluting analytes applying two selective mass transitions. In addition, due to reproducible in-source decarboxylation, the acidic forms of cannabinoids were reliably quantified using mass transitions of the neutral forms. The accuracy given as the bias was below 15% for all analytes. Matrix effects for cannabinoids were studied by spiking Humulus lupulus extracts with the analytes at varying concentrations. APCI did not show susceptibility toward ion suppression or enhancement. In addition, the recovery effect after spiking was between 80 and 120% for terpenes. Further, 55 authentic C. sativa extracts were fully quantified, and the obtained results for the terpene profiles were compared to state-of-the-art gas chromatography coupled to flame ionization detection. Comparable results were achieved, emphasizing the method's applicability for cannabinoids and terpenes. Further, acquired metabolite patterns for C. sativa samples were studied, identifying a relationship between cannabinoid and terpene patterns, as well as the abundance of myrcene in CBD-dominant C. sativa strains.

Development and Validation of UV-VIS Spectrophotometric Method for Estimation of Methylprednisolone from Dissolution Media

A simple, accurate UV-Spectrophotometric method has been developed using a dissolution media, 0.1% Tween 20 as a solvent to determine the Methylprednisolone. At a predetermined λmax of 245 nm, method was proved linear in the range of 5- 40 μg/ml with good correlation coefficient (R2= 0.998) and excellent recovery (between 98 and 101%). This method was successfully applied to the determination of methylprednisolone from dissolution media, 0.1% Tween 20 solution. This method can be employed for the dissolution study of methylprednisolone in injectable suspension.