Construction Of Calibration Curve Research Articles

Direct Determination of Flavanone Isomers in Citrus Juice by Paper Spray Tandem Mass Spectrometry.

A novel and efficient analytical protocol based on paper spray tandem mass spectrometry was developed for the determination of isomeric O-glycoside flavanones in citrus juices and beverages. This approach significantly reduces sample preparation time and solvent consumption compared to traditional chromatographic techniques. By exploiting the unique fragmentation patterns of these compounds, accurate quantification of both diglycosides and their individual isomers (neohesperidoside and rutinose derivatives) was achieved. The method demonstrated excellent analytical performance, with high accuracy, selectivity, and reproducibility. The impact of matrix effects was mitigated through the construction of ratio calibration curves, ensuring reliable quantification in complex matrices. Finally, a simple DPPH experiment to assay the antioxidant activity of each single positional isomer was performed, indicating the superior ability of neohesperidose conjugates. This simplified method offers a valuable tool for quality control, authenticity assessment and the study of health benefits associated with citrus consumption.

Determination of rare earth elements in synthetic calcium phosphates by high-resolution continuum source electrothermal atomic absorption spectrometry

Ceramic, cement and composite biomaterials have been developed based on hydroxyapatites (HA) and tricalcium phosphates (TCP), which are analogous in phase and chemical composition to the mineral component of bone tissue. The crystal structures of HA and TCP are arranged in isomorphic substitutions. Recently, research has focused on the modification of HA and TCP structures with ions of various metals, including rare earth ions (REEs), with the aim of creating materials with a range of beneficial properties for medical applications. REEs are known to have a number of useful properties, including antibacterial, antitumour, catalytic, magnetic and luminescent properties. The replacement of some of the Ca ions in the structures of HA and TCP with REE ions therefore makes it possible to obtain a material with biocompatibility and biological activity, giving it the required properties depending on the REE used and its concentration. In order to achieve the specified properties, it is necessary to control not only the structure (phase composition, lattice parameters of the powders) and the presence of characteristic functional groups, but also the chemical elemental composition. Modifications of hydroxyapatites and tricalcium phosphates containing from one to several different alloying elements are currently being developed. Various analytical methods are used for this purpose, including X-ray, atomic emission and a number of others. This article is devoted to the study of the analytical capabilities of the method of atomic absorption spectrometry with electrothermal atomization and a continuous spectrum source in relation to the determination of Eu and Yb in hydroxyapatites and tricalcium phosphates. The article considers the optimal conditions and modes of analysis, including temperature-time programs, the use of modifiers, the construction of calibration curves, and other factors that can be adjusted for more precise results. The results demonstrated the possibility of simultaneous determination of both Eu and Yb in the concentration range of 0.09 to 2 wt.%, with a relative standard deviation of less than 6 rel.%.

Towards the construction of regional marine radiocarbon calibration curves: an unsupervised machine learning approach

Abstract. Radiocarbon may serve as a powerful dating tool in palaeoceanography, but its accuracy is limited by the need to calibrate radiocarbon dates to calendar ages. A key problem is that marine radiocarbon dates must be corrected for past offsets from either the contemporary atmosphere (i.e. “reservoir age” offsets) or a modelled estimate of the global average surface ocean (i.e. delta-R offsets). This presents a challenge because the spatial distribution of reservoir ages and delta-R offsets can vary significantly, particularly over periods of major marine hydrographic and/or carbon cycle change such as the last deglaciation. Modern reservoir age and delta-R estimates therefore have limited applicability. While forward modelling of past R-age variability has been proposed as a means of resolving this problem, this requires accurate a priori knowledge of past global radiocarbon budget closure (i.e. production, and cycling), which we currently lack. In this context, the construction of empirical regional marine calibration curves could provide a way forward. However, the spatial reach of such calibrations and their robustness subject to (uncertain) temporal changes in climate and ocean circulation would need to be tested. Here, we use unsupervised machine learning techniques to define distinct regions of the surface ocean that exhibit coherent behaviour in terms of their radiocarbon age offsets from the contemporary atmosphere (R ages), regardless of the causes of R-age variability. We apply multiple algorithms (k-means, k-medoids, and hierarchical clustering) to outputs from two different numerical models spanning a range of climate states, forcings, and timescales of adjustment. Comparisons between the cluster assignments across model runs confirm some robust regional patterns that likely stem from constraints imposed by large-scale ocean and atmospheric physics. At the coarsest scale, regions of coherent R-age variability correspond to the major ocean basins. By further dividing basin-scale shape-based clusters into amplitude-based subclusters, we recover regional associations, such as increased high-latitude R ages, or the propagation of R-age anomalies from regions of deep mixing in the Southern Ocean to upwelling sites in the eastern equatorial Pacific, which cohere with known modern oceanographic processes. We show that the medoids (i.e. the most representative locations) for these regional sub-clusters provide significantly better approximations of simulated local R-age variability than constant offsets from the global surface average. This remains true when cluster assignments obtained from one model simulation are applied to simulated R-age time series from another. Further, model-based clusters are found to be broadly consistent with existing reservoir age reconstructions that span the last ∼30 kyr. We therefore propose that machine learning provides a promising approach to the problem of defining regions for which empirical marine radiocarbon calibration curves may eventually be generated.

Uncertainty Evaluation for the Determination of Perfluorinated Compounds in Wastewater Treatment Facility Effluent

This study evaluates the sources of uncertainty in the determination of poly & perfluorinated compounds(PFHxS, PFOS, PFOA) in the effluent of a wastewater treatment facility using LC-MS/MS. The uncertainty sources were identified and, numerically quantified, and the overall uncertainty of the final results was calculated through the synthesis and expansion of uncertainties. The main factors contributing to the combined standard uncertainty were identified as the construction of calibration curves, the reproducibility uncertainty from repeated tests, and the uncertainty associated with sample collection. By contrast, the effects of processes such as the volume filling of 1 mL standards after concentration and the injection of internal standards were found to be negligible. The relative expanded uncertainties for the three perfluorinated compounds were within 7.45%. The contributions to the overall uncertainty from sample collection, calibration curve construction, internal standard injection, volume filling of 1 mL standards, and reproducibility from repeat tests were 1.16~1.62%, 87.11~94.52%, 0.37~0.53%, 0.33~0.46%, 2.87~11.03%, respectively.

Utilizing erythrosine B absorption spectrum shifts for quantitative determination of octreotide and bromocriptine in their pure forms and pharmaceutical formulations. Evaluation of the method greenness

In the present study, two drugs for treating acromegaly are investigated which are either synthetic growth hormone inhibiting hormone (GHIH) or dopamine receptor agonist. Octreotide (OCT) and bromocriptine (BCT) were quantified with a quick, simple, and sensitive spectrophotometric approach in their authentic forms and commercial dosage forms. This approach was based upon formation of ion pair complex between erythrosine B and investigated drugs in an aqueous buffered solution. For OCT determination the higher sensitivity was obtained using ΔA at 525 nm. On the other hand, BCT was estimated using the absorbance at 556 nm. Under optimal conditions for the reaction, construction of calibration curves were performed within concentration range of 0.4–4 µg ml−1 for OCT and 1–9 µg ml−1 for BCT with with low detection limits (0.094 and 0.235 µg ml−1) and low quantitation limits (0.29 and 0.71 µg ml−1) for OCT and BCT respectively. The developed approach was assessed for linearity, accuracy, precision, limits of detection, and limits of quantitation in compliance with ICH validation recommendations. The suggested approaches demonstrated good linearity, as evidenced by determination coefficients (r2) of 0.999 with a slope 0.14 for OCT and 0.9989 with a slope 0.06 for BCT. Additionally, the environmental friendliness of the investigated method was assessed with some of the recent green analytical chemistry metrics.

2D Raman imaging for vibrational and rotational temperature mapping in H2

We showcase a Raman scattering diagnostic for 2D imaging of the rotational and vibrational temperatures of H2. Applications include environments with vibrational-rotational non-equilibrium such as H2-containing supersonic jets and plasma reactors. We image segments of the laser scattering spectrum, containing one or more Raman features, using an ICCD camera that is equipped with one of several bandpass filters. Knowing their transmission spectrum allows the construction of calibration curves that relate the relative intensities of the multi-spectral image to the rotational and vibrational temperatures. Additionally, the absolute intensity indicates the density of H2. We illustrate the capability to independently measure rotational (300–3000 K, ±150 K) and vibrational temperatures (1000–3000 K, ±50 K). The technique is demonstrated on two different H2 microwave plasmas and validated against conventional fitting of 0D and 1D Raman spectra.

DDX21 functions as a potential novel oncopromoter in pancreatic ductal adenocarcinoma: a comprehensive analysis of the DExD box family

BackgroundPancreatic ductal adenocarcinoma (PDAC) is a highly lethal tumor with an ill-defined pathogenesis. DExD box (DDX) family genes are widely distributed and involved in various RNA metabolism and cellular biogenesis; their dysregulation is associated with aberrant cellular processes and malignancies. However, the prognostic significance and expression patterns of the DDX family in PDAC are not fully understood. The present study aimed to explore the clinical value of DDX genes in PDAC.MethodsDifferentially expressed DDX genes were identified. DDX genes related to prognostic signatures were further investigated using LASSO Cox regression analysis. DDX21 protein expression was analyzed using the UALCAN and human protein atlas (HPA) online tools and confirmed in 40 paired PDAC and normal tissues through Tissue Microarrays (TMA). The independent prognostic significance of DDX21 in PDAC was determined through the construction of nomogram models and calibration curves. The functional roles of DDX21 were investigated using gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA). Cell proliferation, invasion, and migration were assessed using Cell Counting Kit-8, colony formation, Transwell, and wound healing assays.ResultsUpregulation of genes related to prognostic signatures (DDX10, DDX21, DDX60, and DDX60L) was significantly associated with poor prognosis of patients with PDAC based on survival and recurrence time. Considering the expression profile and prognostic values of the signature-related genes, DDX21 was finally selected for further exploration. DDX21 was overexpressed significantly at both the mRNA and protein levels in PDAC compared to normal pancreatic tissues. DDX21 expression, pathological stage, and residual tumor were significant independent prognostic indicators in PDAC. Moreover, functional enrichment analysis revealed that Genes co-expressed with DDX21 are predominantly involved in RNA metabolism, helicase activity, ribosome biogenesis, cell cycle, and various cancer-related pathways, such as PI3K/Akt signaling pathway and TGF-β signaling pathway. Furthermore, in vitro experiments confirmed that the knockdown of DDX21 significantly reduced MIA PaCa-2 cell viability, proliferation, migration, and invasion.ConclusionsFour signature-related genes could relatively precisely predict the prognosis of patients with PDAC. Specifically, DDX21 upregulation may signal an unfavorable prognosis by negatively affecting the biological properties of PDAC cells. DDX21 may be considered as a candidate therapeutic target in PDAC.

An ultra-fast ultra-high-performance liquid chromatography-tandem mass spectrometry method for estimating the in vitro metabolic stability of palbociclib in human liver microsomes: In silico study for metabolic lability, absorption, distribution, metabolism, and excretion features, and DEREK alerts screening.

Palbociclib (Ibrance; Pfizer) was approved for the management of metastatic breast cancer characterized by hormone receptor-positive/human epidermal growth factor receptor 2 negative status. The objective of this study was to create a fast, precise, environmentally friendly, and highly sensitive ultra-high-performance liquid chromatography-tandem mass spectrometry approach for quantifying palbociclib (PAB) in human liver microsomes with the application for assessing metabolic stability. The validation features were performed in agreement with the bioanalytical method validation standards outlined by the US Food and Drug Administration. The StarDrop software (WhichP450 and DEREK modules) was used in screening the metabolic lability and structural alerts of PAB. The separation of PAB and encorafenib (as an internal standard) was achieved on a C8 column, employing an isocratic mobile phase. The inter-day and intra-day accuracy and precision ranged from -6.00% to 4.64% and from -2.33% to 3.13%, respectively. The constructed calibration curve displayed a linearity in the range of 1-3000ng/mL. The sensitivity of the established approach was proven by the lower limit of quantification of 0.73ng/mL. The Analytical GREEness calculator results revealed the high level of greenness of the developed method. The PAB's metabolic stability (t1/2 of 18.5 min and a moderate clearance (Clint) of 44.8mL/min/kg) suggests a high extraction ratio medication that matched the WhichP450 software results.

A biosensor monitoring approach for toxic algae: Construction of calibration curves to infer cell numbers in field material

A variety of shellfish toxin-producing Harmful Algal Blooms (HABs) occur every year in coastal temperate waters worldwide. These toxic HABs may cause lengthy (months) harvesting bans of mussels and other suspension feeding bivalves exposed to their blooms. To safeguard public health and the shellfish industry, European Union regulations request periodic monitoring of potentially toxic microalgae in seawater and phycotoxins in live bivalve molluscs from shellfish production areas. Monitoring of other toxic microalgae, e.g., fish killers, is based solely on cell counts. Morphological identification and quantification of microalgal cells with light microscopy is time-consuming, requires a good expertise, and accurate identification to species level (e.g., Pseudo-nitzschia species) may require electron microscopy. Toxicity varies among morphologically similar species; there are toxic and non-toxic strains of the same species. Molecular techniques using ribosomal DNA sequences offer a possibility to identify and detect precisely the potentially toxic genus/species. In an earlier project (MIDTAL), specific probes against rRNA sequences of all HAB taxa, known at the time of the project, affecting shellfish areas worldwide were designed, and those affecting Europe were tested and calibrated against rRNA extracts of clonal cultures and field samples. Microarray technology was adopted to relate to cell numbers the fluorescence signal from the reaction of all target species probes spotted in the microarray slides with those present in a single sample extract. The EMERTOX project aimed to develop a more automatic “Lab on a chip” (LOC) technology, including a non- (cell) disruptive water concentration system and biosensors for HAB cells detection. Here, calibration curves are presented against toxic microalgae (cultures and field samples) causing endemic and emerging toxicity events in Galicia (NW Spain) and Portugal. Results here relating cell numbers to electrochemical signals will be used in an early warning biosensor for toxic algae.

Multifactorial risk prediction analysis of liver metastasis in colorectal cancer: incorporating programmed cell death ligand 1 combined positive score and other factors

BackgroundThe occurrence of liver metastasis significantly impacts the prognosis of colorectal cancer. Existing research indicates that primary tumor location, vascular invasion, lymph node metastasis, and abnormal preoperative tumor markers are risk factors for colorectal cancer liver metastasis. Positive expression of PD-L1(Programmed Cell Death 1 Ligand 1) may serve as a favorable prognostic marker for nasopharyngeal and gastric cancers, where CPS（Combined Positive Score） quantifies the level of PD-L1 expression. Based on previous studies, exploring CPS as a potential risk factor for colorectal cancer liver metastasis and integrating other independent risk factors to establish a novel predictive model for colorectal cancer liver metastasis. MethodsA retrospective analysis was conducted on 437 colorectal cancer patients pathologically diagnosed at Xiangya Second Hospital, Central South University, from January 1, 2019, to December 31, 2021. Data were collected, including CPS, age, gender, primary tumor location, Ki-67 expression, pathological differentiation, neural invasion, vascular invasion, lymph node metastasis, and preoperative tumor markers.The optimal cut-off point for the continuous variable CPS was determined using the Youden index, and all CPS were dichotomized into high and low-risk groups based on this threshold (scores below the threshold were considered high-risk, and those above it were considered low-risk). Univariate logistic regression analysis was employed to identify risk factors for colorectal cancer liver metastasis, followed by the application of multivariate logistic regression analysis to integrate the selected risk factors.The predictive model established was validated through the construction of ROC (Receiver Operating Characteristic) curves, calibration curves, and DCA (Decision Curve Analysis). A nomogram was constructed for visualization purposes. ResultsThe determined cut-off point for PD-L1 CPS was 4.5, with scores below this threshold indicating high risk for colorectal cancer liver metastasis. Additionally, primary tumor origin other than the rectum, presence of pericolonic lymph node metastasis, and abnormal levels of tumor markers CEA and CA199 were identified as independent risk factors for colorectal cancer liver metastasis. The constructed clinical prediction model demonstrated good predictive ability and accuracy, with an area under the ROC curve of 0.871 (95% CI 0.838-0.904). ConclusionThe exploration and validation of CPS as a novel predictor for colorectal cancer liver metastasis were conducted. Based on this, a new clinical prediction model for colorectal cancer liver metastasis was developed by integrating other independent risk factors. The DCA, clinical impact curve, and nomogram graph constructed based on this model have significant clinical implications and provide guidance for clinical practice.

DEVELOPMENT OF CONTROLLED RELEASE FORMULATIONS OF DEXLANSOPRAZOLE TO IMPROVE BIOAVAILABILITY

The present work was aimed to development of controlled release formulations of Dexlansoprazole to improve bioavailability. Dexlansoprazole is the proton pump inhibitor that suppresses gastric acid secretion by specific inhibition of the H+/K+-ATPase in the gastric parietal cell. By acting specifically on the proton pump, Dexlansoprazole blocks the final step in acid production, thus reducing gastric acidity. Construction of calibration curve of Dexlansoprazole and to investigate the drug and polymer interaction studies by FTIR and DSC. To prepare the different controlled release formulations of Dexlansoprazole tablets with different polymers such as acrylic acid polymer such as Carbopol-974P, HPMC grades for prevalence HPMC-K4M, HPMC-K15M, HPMCK100M, Natural Polymers akin to Xanthan gum, Guar gum, Sodium Carboxy Methyl Cellulose, and Pectin by Direct Compression method. Evaluation of Dexlansoprazole pre compression parameters such as Bulk density, Tapped density, Hausner’s ratio, Carr’s index, Angle of repose. Evaluation of post-compression parameters of Dexlansoprazole controlled release tablets such as Weight variation, Hardness, Friability test, Thickness, Drug Content and In-vitro dissolution studies. Evaluation of in-vitro dissolution uniqueness of all the formulations of Dexlansoprazole by using USP dissolution apparatus type-II (paddle). To study the mechanism of drug dissolution by applying kinetic parameters. To perform the stability studies of optimized formulations of Dexlansoprazole as per ICH guidelines.

Laser-induced breakdown spectroscopy of biological tissues: Plasma diagnostics and a comparison of quantification approaches

While calibration-free laser-induced breakdown spectroscopy (CF-LIBS) is a well-known technique, its applications to biosamples, particularly soft tissues, remain limited. Our research focuses on the plasma diagnostics and CF-LIBS analysis of fatty and non-fatty samples (zooplankton, fish, and plants). The selection of zooplankton as an object was motivated by previously reported anomalous accumulation of certain chemical elements. It was observed that temperature and electron number density of laser plasmas induced on these samples, as determined with the use of Mg I-II and Hα emission lines, do not appear to be systematically affected by minor element composition. Plasma conditions across varying samples are most similar at early stages of plasma evolution.Our investigation yielded four sets of analytical outcomes: calibration-based (CB); calibration-free calculations without (CF1) and with (CF2) spatial resolution, as well as data based on the emission from the plasma central zone (CF1a). The same set of analytical lines of B, Ca, K, Li, Mg, Na, P, and Sr was used across all the four cases. To reduce error for CF-LIBS calculations, each element was measured independently from the others using element-to‑carbon (E/C) ratios. Conversely, in non-fatty samples, E/Mg ratios were shown to fit the Local Thermodynamic Equilibrium for all considered transitions. For a more nuanced evaluation of our results, we have proposed a new variant of the distance metric termed the Accuracy Factor (AF). This metric offers a lucid representation of the method accuracy (for instance, AF = 1.5 indicates that the results are accurate within an average factor of 1.5, i.e., they range between 0.67 and 1.5 times the respective certified values).The performance of the CF technique for our biological samples aligns closely with calibration-based LIBS. Using CF-LIBS, we have successfully quantified Li, an element for which constructing calibration curves proved untenable. Our findings underscore that spatially resolved measurements yield more accurate results compared to spatially-integrated measurements, especially for fatty samples.

Estimation of Measurement Uncertainty for Nonylphenol Compounds in Industrial Wastewater

This study focuses on quantifying the impact of various factors on nonylphenol analysis and identifying the key contributors affecting the analytical outcomes. We calculated the measurement uncertainty arising from the analysis process using GC-MS, aiming to pinpoint uncertainty sources, quantify them numerically and then calculated the overall uncertainty through uncertainty synthesis. The results revealed that factors such as calibration curve construction, internal standard injection, and reproducibility through repeated testing significantly influenced the synthetic standard uncertainty. Negligible effects were observed during processes, involving concentration and filling the standard volume post-purification, as well as during sample collection. The relative expanded uncertainty for nonylphenol concentration was within 4.6%. The uncertainty contributions from each step were as follows: sample collection, calibration curve construction, injection of internal standards, filling of the 1 mL standard volume, and reproducibility from repeated testing accounted for 0.0%, 92.7%, 4.0%, 0.1%, and 3.2% of the total uncertainty, respectively.

A novel approach for constructing the calibration curve applied in determining the thickness of different types of materials

A solution using a gamma-ray beam to measure the thickness of materials with different elemental composition is necessary as this issue has not been previously addressed. Traditionally, a linear calibration curve is only utilized to determine the thickness of a specific material. This means that multiple separate calibration curves must be used when measuring the thickness of different types of materials, which results in increased time and cost. This study proposes a novel aproach for constructing calibration curves that can be applied to measure the thickness of materials with different elemental composition. The methodology and mathematical formalism are described. For each material type, the linear calibration curve (LCC) of lnR (R represents the ratio of areas under the transmission peak for measurements with and without a sample) versus thickness of material plate has been constructed. The slope of this linear calibration curve, depending on the linear attenuation coefficient (LAC) of the material, enables easy determination of material thicknesses. To assess accuracy, we conducted thickness measurements on reference material plates including aluminum, steel, copper, and graphite. The obtained results indicate that relative deviations between measured and reference thicknesses are below 2.39%, confirming the usefulness and reliability of the proposed approach in measuring thickness for different types of materials.

Digital PCR as a Highly Sensitive Diagnostic Tool: a Review

Nowadays digital PCR (dPCR) is a nucleic acid quantification method widely used in genetic analysis. One of the most significant advantages of dPCR over other methods is the possibility for absolute quantitative determination of genetic material without construction of calibration curves, which allows one to detect even single molecules of nucleic acids, and, hence, early diagnosis of diseases. A specific characteristic of dPCR is the detection of the analyzed biological object in each microreaction, followed by the presentation of the analysis results in a binary system, thereby giving the method name. The key aspects of developing the dPCR method, i.e. from the first devices based on microfluidic chip technology to modern systems capable of measuring a target at a concentration of up to 1 in 100 000 copies were shown in the current work. We analyzed the data on the detection of various pathogens using dPCR, as well as summarized various study results demonstrating the innovativeness of this method “point-of-care”. Both the possibilities of multiplex dPCR analysis and its potential in clinical practice were presented. The review also addresses the issue of the dPCR role in the development of non-invasive methods for oncological diseases to be analyzed. Possible ways of developing dPCR technology were emphasized, including the use as a “point-of-care” systems.

Dual-mode highly selective colorimetric and smartphone-based paper sensors utilizing silver nanoparticles for ultra-trace level omeprazole detection in complex matrices

The present work focuses on the synthesis and optimization of highly stable, bare silver nanoparticles (AgNPs) as colorimetric sensor for trace-level detection of omeprazole. A novel approach combining AgNPs-based paper sensor and smartphone technology enables real-time analysis of omeprazole. The color change observed by the naked eye and shift in localized surface plasmon resonance (LSPR) were used to construct calibration curves. Both LSPR-based colorimetric sensing and paper-based sensing approaches were utilized for omeprazole detection in complex matrices. The limits of detection (LODs) were determined as 15 nM and 240 nM, with linear dynamic ranges of 0.05–40 µM and 0.1–50 µM, respectively. Recovery studies demonstrated % recoveries within the acceptable range of 90–110% and relative standard deviation (RSD) below 2%. Detailed characterizations including Fourier-Transform Infrared - (FTIR) Spectroscopy, Dynamic Light Scattering (DLS), zeta potential, Atomic Force Microscopy (AFM), and Field-Emission Scanning Electron Microscopy (FE-SEM) provided insights into sensing mechanism. This work offers a promising and practical solution for real-time omeprazole analysis with potential applications extending beyond pharmaceutical formulations. The developed colorimetric sensor based on AgNPs demonstrates high stability, sensitivity, and versatility, making it suitable for on-site and point-of-care omeprazole detection in various samples, including serum, plasma, urine, sea water, and tap water.

Assisted Reductive Amination for Quantitation of Tryptophan, 5-Hydroxytryptophan, and Serotonin by Ultraperformance Liquid Chromatography Coupled with Tandem Mass Spectrometry.

Herein, we used isotopic formaldehyde and sodium cyanoborohydride via reductive amination to label two methyl groups on primary amine to arrange the standards (h2-formaldehyde-modified) and internal standards (ISs, d2-formaldehyde-modified) of tryptophan and its metabolites, such as serotonin (5-hydroxytryptamine) and 5-hydroxytryptophan. These derivatized reactions with a high yield are very satisfactory for manufacturing standards and ISs. This strategy will generate one or two methyl groups on amine to create different mass unit shifts with 14 vs. 16 or 28 vs. 32 in individual compounds for biomolecules with amine groups. In other words, multiples of two mass units shift are created using this derivatized method with isotopic formaldehyde. Serotonin, 5-hydroxytryptophan, and tryptophan were used as examples to demonstrate isotopic formaldehyde-generating standards and ISs. h2-formaldehyde-modified serotonin, 5-hydroxytryptophan, and tryptophan are standards to construct calibration curves, and d2-formaldehyde-modified analogs such as ISs spike into samples to normalize the signal of each detection. We utilized multiple reaction monitoring modes and triple quadrupole mass spectrometry to demonstrate the derivatized method suitable for these three nervous biomolecules. The derivatized method demonstrated a linearity range of the coefficient of determinations between 0.9938 to 0.9969. The limits of detection and quantification ranged from 1.39 to 15.36 ng/mL.

Validation of a rapid microbiological method for the detection and quantification of the Burkholderia cepacia complex in an antacid oral suspension.

Despite the broad adoption of Soleris® technology in the food industry as semiquantitative method, they are almost completely unexplored in the pharmaceutical industry as a quantitative method for quantification of Burkholderia cepacia complex. The efficacy of an automated growth-based system for a quantitative determination of the Burkholderia cepacia complex in an antacid oral suspension was studied. The main purpose of this validation study was to prove that the alternative method's entire performance is not inferior to the conventional method for a quantitative determination of Burkholderia cepacia complex. The antacid oral suspension's preservatives were neutralized, leading to the Burkholderia complex's recovery by means of the alternative method and the reference method. A calibration curve was generated for each strain by plotting DTs relative to the corresponding log CFU values. An equivalence of results was done through the construction of calibration curves that allowed the establishment of numerically equivalent results between the enumeration data from the reference method and the alternative method. Thus following the guidelines of USP, essential validation parameters were shown, such as equivalence of results (CC > 0.95), linearity (R2 >0.9025), accuracy (% recovery >70%), operating range, precision and ruggedness (DS < 5 and CV < 35%), specificity (inclusivity and exclusivity), limit of detection, and limit of quantification. It was shown that all the test results obtained from the alternative method were in statistical agreement with the standard method. Thus this new technology was found to meet all the validation criteria needed to be considered to be an alternative method for the quantification of the Burkholderia complex in the antacid oral suspension tested. mplementation of alternative methods can offer benefits in execution and automation while improving accuracy, sensitivity, and precision and reduce the microbiological process time compared to the traditional ones.

High-Throughput Nanoliter Sampling and Direct Analysis of Biological Fluids Using Droplet Imbibition Mass Spectrometry.

A high-throughput droplet imbibition mass spectrometry (MS) experiment is reported for the first time that allows direct analysis of ultra-small volumes of complex mixtures. In this experiment, an array of optimized tips of glass capillaries containing the analyte solution is sampled by rapidly moving charged microdroplets, which picks up (i.e., imbibes) the analyte and transfers it to a proximal mass spectrometer. The advantages associated with this droplet imbibition experiment include (1) ultra-small sample consumption (1.3 nL/min), which reduces the matrix effect in complex mixture analysis, and (2) high surface activity, which eliminates ion suppression effects caused by competition for the space charge on the droplet surface. Collectively, the enhanced surface effect and small flow rates dramatically increase the sensitivity of the droplet imbibition MS approach. This was experimentally shown by constructing calibration curves for cocaine analysis in human raw urine and whole blood, achieving 2 and 7 pg/mL limits of detection, respectively. The high-throughput feature was demonstrated by analyzing five structurally different compounds in 20 s intervals. With the measured flow rate of 1.3 nL/min on a 5 μm glass tip size, the results described in the current study showcase droplet imbibition MS to be a powerful and high-throughput alternative for conventional nano-electrospray ionization (flow rate <100 nL/min), which is the most efficient method for transferring small sample volumes to mass spectrometers.

Nomogram Prediction Model of the Severity of CAP Patients Based on Blood Indicators.

Community-acquired pneumonia (CAP) is a common cause of hospitalization, characterized by high mortality, morbidity, and cost and has serious human health implications. Various scoring criteria have been used to predict the severity of pneumonia, including the CURB-65 score, Pneumonia Severity Index (PSI) score, and Severe Community-Acquired Pneumonia (SCAP) score. However, these scoring criteria have shortcomings such as low sensitivity, cumbersome clinical application, and limited application. This study aimed to construct a nomogram model to predict the severity of CAP patients by blood indicators. This is a retrospective study. Patients with CAP were enrolled and then tested by routine blood, coagulation series, biochemical and inflammatory indicators, and general information such as imaging findings and disease history of the patients were recorded. The main observation was the progression of the patients' disease. Univariate analysis and binary logistic regression analysis were used to explore the independent risk factors for the severity of CAP patients, followed by plotting a nomogram to obtain the prediction model and constructing calibration curves to assess the authenticity and accuracy of the prediction model. Finally, the sensitivity, specificity, and other evaluation indexes were calculated by the receiver operating characteristic curve (ROC) to evaluate the clinical application value of the nomogram prediction model. Univariate analysis and binary logistic regression analysis of 277 hospitalized patients yielded platelet to lymphocyte ratio (PLR) and serum amyloid A (SAA) as independent risk factors for the severity of CAP patients. The AUC of the nomogram model for PLR and SAA was 0.889 (95% CI 0.845 - 0.932). The sensitivity was 77.3%, and the specificity was 85.3%, which had an excellent predictive value. The nomogram model based on PLR and SAA to predict the severity of CAP patients has a high specificity and sensitivity.