Slope Of Calibration Curve Research Articles

Facile Electrical DNA Genosensor for Human Papillomavirus (HPV 58) for Early Detection of Cervical Cancer

For decades, a Pap smear test has been applied as a conventional method in detecting Human Papillomavirus caused cervical cancer. False-positive results were also recorded while using it as conventional method. Current biosensor such as Hybrid (II) Capture resulted in higher time consumption and cost. s Meanwhile, in this study we provided facile, mini, rapid, highly sensitive, eco-friendly, and cost-effective sensing system focusing on HPV strain 58 (HPV58) in a nano-size lab-on-chip technology genosensor. 30-mer of virus ssDNA designed and analyzed as a probe via bioinformatics tools such as GenBank, Basic Local Alignment Searching Tools (BLAST) and ClustalW. Nanotechnology-developed colloidal Gold-nanoparticles (AuNPs) are used in the biosensor fabrication to produce high stability and electron efficient transmission during electrical measurement. AuNPs-APTES modified on active sites of IDEs, followed by immobilization of specific probe ssDNA for HPV 58. Hydrogen binding during hybridization with its target produce electrical signals measured by KEITHLEY 2450 (Source Meter). The genosensor validated with different types of targets such as complimentary, non-complementary and single mismatch oligonucleotides. The serial dilution of target concentration has been experimented triplicate (n=3) range from 1fM to 10μM. The slope of calibration curve resulted 2.389E-0 AM-1 with regression coefficient (R2) = 0.97535.

Factors related to the occurrence of fetal birth defects and the construction of a Nomogram model.

To explore the influencing factors of fetal birth defects (BD) and construct a nomogram model. A total of 341 newborns admitted to Meizhou people's hospital from September 2021 to September 2023 were randomly grouped into a modeling group (239 cases) and a validation group (102 cases). The modeling group fetuses were separated into BD and non-BD groups. Multivariate logistic regression analyzed risk factors for BD; R software constructed a nomogram model; Receiver operating characteristic (ROC) curve evaluated the model's discrimination for BD. The top 5 types of BD were congenital heart disease, polydactyly/syndactyly, cleft lip/palate, ear malformation, and foot malformation, with incidence rates of 23.81%, 20.63%, 12.70%, 11.11%, and 7.94%, respectively. BD incidence was 26.36% (63/239). Significant differences between BD and non-BD groups were found in maternal age, gestational age, history of adverse pregnancy/childbirth, gestational hypertension, adverse emotions during pregnancy, and folic acid intake duration (P<0.05). Logistic regression showed maternal age (OR: 4.125), gestational age (OR: 3.066), adverse pregnancy history (OR: 10.628), gestational hypertension (OR: 5.658), adverse emotions (OR: 5.467), and folic acid intake duration (OR: 4.586) were risk factors for BD (P<0.05). The modeling group's ROC AUC was 0.938, calibration curve slope close to 1, H-L test =8.342, P=0.692; external validation AUC was 0.961, calibration slope close to 1, H-L test =7.634, P=0.635. Identified risk factors include maternal age, gestational age, adverse pregnancy history, gestational hypertension, adverse emotions, and folic acid intake duration. The nomogram model shows good discrimination and consistency for evaluating neonatal BD risk.

Development of a GC-MS Method for the Analysis of Selected Opioids in Human Hair Samples

Background: Hair samples are recognized as alternative biological specimens in forensic and clinical toxicology for detecting drug abuse and poisoning. Forensic testing for opioids in hair has become a useful diagnostic measure for assessing chronic drug usage through segmental analysis. However, accurate, sensitive and specific analytical methods are needed. The aim of this study was to introduce a simple, sensitive and specific GC-MS method for the identification and quantitation of selected and commonly abused opioids (tramadol, methadone, morphine, and codeine) in hair samples. Methods: After external decontamination, a 50 mg portion of powdered hair sample was combined with hydrochloric acid (0.1 M) and incubated on a magnetic stirrer at 56°C for 16 hours. Then, 1 mL of sodium hydroxide (0.1 M) and 2 mL of phosphate buffer (1 M, pH=8.4) were added. Chloroform-isopropanol (ratio: 80:20 V/V) was utilized as the extracting solvent and the sample was homogenized and centrifuged for 5 minutes (at 3500 rpm). After centrifugation, the organic phase was dried using dry nitrogen gas. The sample was derivatized with N-methyl-N-(trimethylsilyl) trifluoroacetamide (MSTFA). The blank, standards, and real samples were subsequently analyzed by GC-MS.Results: The limits of detection in the linearity experiments ranged from 0.12 to 0.21 ng/mg. According to the validation results, the method exhibited linearity in the concentration range of 0.1-2.5 ng/mg for all analytes, with calibration curve slopes ranging from R2=0.98 to 0.99. Good inter and intra-day precision relative standard deviations (RSDs) were observed to be &lt;3.5% for all compounds. Extraction efficiency varied from 91.8 to 102.4%. Conclusion: The validation and analysis of actual samples indicate that this method is straightforward, sensitive, and specific for the analysis of opioids in routine hair analysis.

Matrix effects in ultra-high performance supercritical fluid chromatography-mass spectrometry analysis of vitamin E in plasma: The effect of sample preparation and data processing

The approaches to matrix effects determination and reduction in ultra-high performance supercritical fluid chromatography with mass spectrometry detection have been evaluated in this study using different sample preparation methods and investigation of different calibration models. Five sample preparation methods, including protein precipitation, liquid-liquid extraction, supported liquid extraction, and solid phase extraction based on both “bind and elute” and “interferent removal” modes, were optimized with an emphasis on the matrix effects and recovery of 8 forms of vitamin E, including α-, β-, γ-, and δ-tocopherols and tocotrienols, from plasma. The matrix effect evaluation included the use and comparison of external and internal calibration using three models, i.e., least square with no transformation and no weighting (1/x0), with 1/x2 weighting, and with logarithmic transformation. The calibration model with logarithmic transformation provided the lowest %-errors and the best fits. Moreover, the type of the calibration model significantly affected not only the fit of the data but also the matrix effects when evaluating them based on the comparison of calibration curve slopes. Indeed, based on the used calibration model, the matrix effects calculated from calibration slopes ranged from +92% to – 72% for α-tocopherol and from −77% to +19% in the case of δ-tocotrienol. Thus, it was crucial to calculate the matrix effect by Matuszewski's post-extraction approach at six concentration levels. Indeed, a strong concentration dependence was observed for all optimized sample preparation methods, even if the stable isotopically labelled internal standards (SIL-IS) were used for compensation. The significant differences between individual concentration levels and compounds were observed, even when the tested calibration range covered only one order of magnitude. In methods with wider calibration ranges, the inappropriate use of calibration slope comparison instead of the post-extraction addition approach could result in false negative results of matrix effects. In the selected example of vitamin E, solid-phase extraction was the least affected by matrix effects when used in interferent removal mode, but supported liquid extraction resulted in the highest recoveries. We showed that the calibration model, the use of a SIL-IS, and the analyte concentration level played a crucial role in the matrix effects. Moreover, the matrix effects can significantly differ for compounds with similar physicochemical properties and close retention times. Thus, in all bioanalytical applications, where different analytes are typically determined in one analytical run, it is necessary to carefully select the data processing in addition to the method for the sample preparation, SIL-IS, and chromatography.

Development and Validation of a Bayesian Network Predicting Intubation Following Hospital Arrival Among Injured Children

BackgroundInadequate airway management can contribute to preventable trauma deaths. Current machine learning tools for predicting intubation in trauma are limited to adult populations and include predictors not readily available at the time of patient arrival. We developed a Bayesian network to predict intubation in injured children and adolescents using observable data available upon or immediately after patient arrival. MethodsWe obtained patient demographic, injury, resuscitation, and transportation characteristics from trauma registries from four American College of Surgeons-verified level 1 pediatric trauma centers from January 2010 through December 2021. We trained and validated a Bayesian network to predict emergent intubation after pediatric injury. We evaluated model performance using the area under the receiver operating and calibration curves. ResultsThe final model, TITAN (Timing of Intubation in Trauma Analysis Network), incorporated five factors: Glasgow Coma Scale, mechanism of injury, injury type (e.g., penetrating, blunt), systolic blood pressure, and age. The model achieved an area under the receiver operating characteristic curve of 0.83 (95% CI 0.80, 0.85) and had a calibration curve slope of 0.98 (95% CI 0.67, 1.29). TITAN had high specificity (98%), negative predictive value (97%), and accuracy (96%) at a binary probability threshold of 22.6%. ConclusionThe TITAN Bayesian network predicts the risk of intubation in pediatric trauma patients using five factors that are observable early in trauma resuscitation. Prospective validation of the model performance with patient outcomes is needed to assess real-life application benefits and risks. Level of EvidencePrognostic and Epidemiological, Level III.

Techniques for quantification of organochlorine pesticides from a validated method by using gas chromatography-electron capture detector

Organochlorine pesticides (OCPs) are persistent organic compounds found in aquatic environments worldwide. A well-validated and well-established analytical method is crucial for detecting OCPs in the environment. In this study, an analytical method for quantifying OCPs in water was developed and evaluated. Here, the range of linearity, reproducibility, uncertainty, specificity, method detection limits (MDL), and special emphasis on detection and quantitation limits were assessed. Recovery studies were performed to measure the accuracy and precision of the method. This method exhibited excellent linearity in the range of 2.5–20 μg/L for all compounds. As none of the targeted compounds was detected in the chromatograms of the blank sample with no baseline noise, the limits of detection (LOD) and limits of quantification (LOQ) were determined using the linear regression method, external calibration curve slope, and laboratory fortified blank-based detection. All compounds showed different LOD and LOQ values, depending on the approach used. In particular, endosulfan sulfate, methoxychlor, endrin ketone, H. epoxide, heptachlor, and 4,4ʹ-DDT exhibited high detection limits. The recovery percentage of the 15 compounds at 5 μg/L spiked concentration was between 50 and 150 %, which is consistent with the accuracy of the APHA method. Except for endosulfan sulfate, the relative standard deviations of all other compounds were below 20 %, indicating good precision. This method has also been applied to real water samples. This validation technique is reliable, sensitive, simple, rapid, easy to comprehend, and reproducible. The application of this method in the real water samples was also conducted. Only α-BHC and γ-Chlordane were detected in the water sample.

Establishment of Risk Nomogram Model of Postpartum Hemorrhage After Second Cesarean Section.

To establish and evaluate a nomogram model for predicting the risk of postpartum hemorrhage in second cesarean section. A total of 440 parturients who underwent the second cesarean section surgery and were registered in our hospital from August 2019 to July 2021 were selected as the study subjects. They were randomly divided into 220 modeling group and 220 validation group based on simple randomization. The two groups were divided into postpartum hemorrhage group and postpartum non bleeding group according to whether postpartum hemorrhage occurred. In the modeling group, the incidence of postpartum hemorrhage in the second cesarean section was 15.00%; the Logistic regression model showed that placenta previa, operation time, prenatal anemia, placenta accreta, uterine inertia were the independent risk factors of postpartum hemorrhage in the second cesarean section (P < 0.05). ROC results showed that AUC of predicting the risk of postpartum hemorrhage in the second cesarean section was 0.824. The slope of calibration curve is close to 1, Hosmer-Lemeshow goodness of fit test showed x2= 7.585, P = 0.250. The external verification results show that the AUC is 0.840, and the predicted probability of the calibration curve is close to the actual probability. Based on the five risk factors of postpartum hemorrhage in the second cesarean section, including placenta previa, operation time, prenatal anemia, placenta accreta and uterine inertia, the nomogram model for predicting the risk of postpartum hemorrhage in the second cesarean section has good accuracy and differentiation.

A prediction model for prognosis of nephrotic syndrome with tuberculosis in intensive care unit patients: a nomogram based on the MIMIC-IV v2.2 database.

Currently, a scarcity of prognostic research exists that concentrates on patients with nephrotic syndrome (NS) who also have tuberculosis. The purpose of this study was to assess the in-hospital mortality status of NS patients with tuberculosis, identify crucial risk factors, and create a sturdy prognostic prediction model that can improve disease evaluation and guide clinical decision-making. We utilized the Medical Information Mart for Intensive Care IV version 2.2 (MIMIC-IV v2.2) database to include 1,063 patients with NS complicated by TB infection. Confounding factors included demographics, vital signs, laboratory indicators, and comorbidities. The Least Absolute Shrinkage and Selection Operator (LASSO) regression and the diagnostic experiment the receiver operating characteristic (ROC) curve analyses were used to select determinant variables. A nomogram was established by using a logistic regression model. The performance of the nomogram was tested and validated using the concordance index (C-index) of the ROC curve, calibration curves, internal cross-validation, and clinical decision curve analysis. The cumulative in-hospital mortality rate for patients with NS and TB was 18.7%. A nomogram was created to predict in-hospital mortality, utilizing Alb, Bun, INR, HR, Abp, Resp., Glu, CVD, Sepsis-3, and AKI stage 7 days. The area under the curve of the receiver operating characteristic evaluation was 0.847 (0.812-0.881), with a calibration curve slope of 1.00 (0.83-1.17) and a mean absolute error of 0.013. The cross-validated C-index was 0.860. The decision curves indicated that the patients benefited from this model when the risk threshold was 0.1 and 0.81. Our clinical prediction model nomogram demonstrated a good predictive ability for in-hospital mortality among patients with NS combined with TB. Therefore, it can aid clinicians in assessing the condition, judging prognosis, and making clinical decisions for such patients.

Quantification of Antiviral Drug Tenofovir (TFV) by Surface-Enhanced Raman Spectroscopy (SERS) Using Cumulative Distribution Functions (CDFs).

Surface-enhanced Raman spectroscopy (SERS) is an ultrasensitive spectroscopic technique that generates signal-enhanced fingerprint vibrational spectra of small molecules. However, without rigorous control of SERS substrate active sites, geometry, surface area, or surface functionality, SERS is notoriously irreproducible, complicating the consistent quantitative analysis of small molecules. While evaporatively prepared samples yield significant SERS enhancement resulting in lower detection limits, the distribution of these enhancements along the SERS surface is inherently stochastic. Acquiring spatially resolved SERS spectra of these dried surfaces, we have shown that this enhancement is governed by a power law as a function of analyte concentration. Consequently, by definition, there is no true mean of SERS enhancement, requiring an alternative approach to achieve reproducible quantitative results. In this study, we introduce a new method of analysis of SERS data using a cumulative distribution function (CDF). The antiviral drug tenofovir (TFV) in an aqueous matrix was quantified down to a clinically relevant concentration of 25 ng/mL using hydroxylamine-reduced silver colloids evaporated to dryness. The data presented in this study provide a rationale for the benefits of combining a novel statistical approach using CDFs with simple and inexpensive experimental techniques to increase the precision, accuracy, and analytical sensitivity of aqueous TFV quantification by SERS. TFV calibration curves generated using CDF analysis showed higher analytical sensitivity (in the form of a normalized calibration curve average slope increase of 0.25) compared to traditional SERS intensity calculations. A second aliquot of nanoparticles and analyte dried on the SERS surface followed by CDF analysis showed further analytical sensitivity with a normalized calibration curve slope increase of 0.23 and decreased variation among replicates represented by an average standard deviation decrease of 0.02 with a second aliquot. The quantitative analysis of SERS data using CDFs presented here shows promise to be a reproducible method for quantitative analysis of SERS data, a significant step toward implementing SERS as an analytical method in clinical and industrial settings.

Determination of Polystyrene Microplastic in Soil by Pyrolysis – Gas Chromatography – Mass Spectrometry (pyr-GC-MS)

Pyrolysis-gas chromatography-mass spectrometry (pyr-GC-MS) is emerging as a promising alternative for the detection and quantification of microplastic pollution. For a robust quantification it is essential to improve our understanding of interferences in the pyrolysis of microplastics. Here we investigate the effects of different soil matrices, mainly differing by their organic carbon content (Corg, 1.0–13.6%), and of the polymer molecular weight (Mw) on the pyr-GC-MS analysis of polystyrene (PS) microplastics. In addition, we evaluated the effectiveness of adding poly(4-fluorostyrene) (PSF) as internal standard to circumvent the matrix effects. The three main markers of PS pyrolysis, i.e., styrene, styrene-dimer and styrene-trimer, were monitored. The ratio between the dimer and the trimer significantly varied between the matrices and tended to decrease with the increasing of the Corg in the soil, mainly due to an increased trimer formation. A strong matrix effect affected the slope of the calibration curves by 2 to 8-fold and was correlated with the Corg in the soils. This effect was mitigated when the areas of the markers were normalized by the area of the corresponding marker of PSF. PS of low Mw (Mw 35,000) presented a reduced formation of the three markers compared to PS of high Mw (Mw 400,000), and styrene-dimer was proportionally less formed than the other two markers. Differences in the slopes of calibration curves depended on the marker chosen, highlighting the relevance of selecting the pyrolysis marker in the quantification of microplastics using pyr-GC-MS.

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.

Prospective validation of a risk score to predict pacemaker implantation after transcatheter aortic valve replacement.

The need for pacemaker is a common complication after transcatheter aortic valve replacement (TAVR). We previously described the Emory Risk Score (ERS) to predict the need for new pacemaker implant (PPM) after TAVR. Metrics included in the score are a history of syncope, pre-existing RBBB, QRS duration ≥140 ms, and prosthesis oversizing ≥16%. To prospectively validate the previously described risk score. We prospectively evaluated all patients without pre-existing pacemakers, ICD, or pre-existing indications for pacing undergoing TAVR with the Edwards SAPIEN 3 prosthesis at our institution from March 2019 to December 2020 (n = 661). Patients were scored prospectively; however, results were blinded from clinical decision-making. The primary endpoint was PPM at 30 days after TAVR. Performance of the ERS was evaluated using logistic regression, a calibration curve to prior performance, and receiver operating characteristic (ROC) analysis. A total of 48 patients (7.3%) had PPM after TAVR. A higher ERS predicted an increased likelihood of PPM (OR 2.61, 95% CI: 2.05-3.25 per point, p < 0.001). There was good correlation between observed and expected values on the calibration curve (slope = 1.04, calibration at large = 0.001). The area under the ROC curve was 0.81 (95% CI [0.74-0.88], p < 0.001). The ERS prospectively predicted the need for PPM in a serial, real-world cohort of patients undergoing TAVR with a balloon-expandable prosthesis, confirming findings previously described in retrospective cohorts. Notably, the prospective performance of the score was comparable with that of the initial cohorts. The risk score could serve as a framework for preprocedural risk stratification for PPM after TAVR.

Size Uncertainty in Individual Nanoparticles Measured by Single Particle Inductively Coupled Plasma Mass Spectrometry.

Single particle inductively coupled plasma mass spectrometry has been used for size measurements of individual nanoparticles (NPs). Here, uncertainties in size analysis based upon two calibration approaches were evaluated: (i) the use of particle size standard and (ii) the use of ion standard solution. For particle size standard approach, the source of uncertainty to determine the target NP diameter was related to the variation in the signal intensities of both target NPs and particle size standard, and the size distribution of the particle size standard. The relative uncertainties of the 50 nm silver NP as the target were 15.0%, 9.9%, and 10.8% when particle size standards of 30 nm, 60 nm, and 100 nm silver NPs were used, respectively. As for the ion standard solution approach, the sources of uncertainty were the concentration of working standard solution, sample flow rate, transport efficiency, slope of calibration curve, and variation in the signal intensity of the ion standard solution and of the target NPs. The relative uncertainties for the 50 nm silver NP were 18.5% for 1 ng/g, 7.6% for 10 ng/g, and 4.7% for 100 ng/g solutions. The lower uncertainty obtained with a high concentration working standard solution is recommended to improve precision on particle size determinations by spICP-MS.

Synthesis of N-acylated pyrazolines: Spectroscopic, crystallographic, Hirshfeld Surface, lead sensing and theoretical studies

N-Acylated-2-pyrazolines (NA2Pyr) were synthesized from chalcone and hydrazine hydrate under one pot cyclocondensation in the presence of propionic acid and trifluoroacetic acid respectively. The structures were determined using FT-IR, 1H NMR, 13C NMR spectral analyses, as well as single crystal diffraction study (Sc-XRD). An effective metal ion sensor (Lead ion) with a flat glassy carbon electrode (GCE) was produced for prospective use by coupling a conducting coating binder (PEDOT:PSS) with a thin-layer NA2Pyr modified electrode (NA2Pyr/GCE). Linear sweep voltammetry was used to detect lead (Pb2+) ions in phosphate aqueous phase. The sensitivity (11,867 uAnM−1cm−2) of the chemical sensor probe was measured utilizing the calibration curve slope and the adjusted electrode active surface area. The linear dynamic range (LDR: 0.01 nM to 10.0 mM) was computed using the calibration plot's maximal linearity line. The detection limit (0.008 nM) was calculated by including 3σ/m (where σ is the standard deviation of the blank response and m is the slope of the calibration curve). The novel electrochemical method is dependable and effective technique for detecting heavy metal ions as a selective lead-sensor for the protection of large-scale medical, biochemical, and environmental fields. Density functional theory (TD-DFT/B3LYP/6-311++G(d,p) was used to computed FMO computations and further study using the optimized geometric parameters of the ground state molecules. According to the predicted energies for HOMO and LUMO, in which the charge of molecule is conveyed, and MEP map, the chemically reactive zone suitable for drug action was identified. The Electron Localization Function (ELF), Non-Bonding Orbitals, Excitation Energies, AIM Charges, and Fukui Functions are also calculated. The docking study contributed to the analysis of EGFR protein binding.

Headspace detection of ethanethiol in wine by cobalt phthalocyanine modified screen-printed carbon electrodes

The formation of thiols has a notable and detrimental sensory impact, especially in the aroma of bottled wines. Their detection in wine is of great interest to avoid important economic and image losses for wineries. This work reports the study of different cobalt phthalocyanine/nanomaterials-based sensors for the headspace detection of volatile thiols. The amperometric procedure based on the use of carbon sensors simply modified with cobalt phthalocyanine showed the best performance. Under the optimum conditions of applied potential, +0.8 V, and pH of the supporting electrolyte, 2.6, this procedure shows a reproducibility of 7% (n = 5) in terms of relative standard deviation of the slopes of calibration curves built in the concentration range from 9.9 to 82.6 μg/L, a capability of detection of 12.5 μg/L and a decision limit of 6.5 μg/L (α = β = 0.05). The use of this electrocatalytic material and the headspace measurements reduce interferents, increasing the selectivity of the procedure, which allows the easy and successful quantification of ethanethiol in white and red wines.

Cardiovascular Risk Prediction in Men and Women Aged Under 50 Years Using Routine Care Data.

Background Prediction models for risk of cardiovascular events generally do not include young adults, and cardiovascular risk factors differ between women and men. Therefore, this study aimed to develop prediction models for first-ever cardiovascular event risk in men and women aged 30 to 49 years. Methods and Results We included patients aged 30 to 49 years without cardiovascular disease from a Dutch routine care database. Outcome was defined as first-ever cardiovascular event. Our reference models were sex-specific Cox proportional hazards models based on traditional cardiovascular predictors, which we compared with models using 2 predictor subsets with the 20 or 50 most important predictors based on the Cox elastic net model regularization coefficients. We assessed the C-index and calibration curve slopes at 10 years of follow-up. We stratified our analyses based on 30- to 39-year and 40- to 49-year age groups at baseline. We included 542 141 patients (mean age 39.7, 51% women). During follow-up, 10 767 cardiovascular events occurred. Discrimination of reference models including traditional cardiovascular predictors was moderate (women: C-index, 0.648 [95% CI, 0.645-0.652]; men: C-index, 0.661 [95%CI, 0.658-0.664]). In women and men, the Cox proportional hazard models including 50 most important predictors resulted in an increase in C-index (0.030 and 0.012, respectively), and a net correct reclassification of 3.7% of the events in women and 1.2% in men compared with the reference model. Conclusions Sex-specific electronic health record-derived prediction models for first-ever cardiovascular events in the general population aged <50 years have moderate discriminatory performance. Data-driven predictor selection leads to identification of nontraditional cardiovascular predictors, which modestly increase performance of models.

Assessment of collagen content in fish skin - development of a flow analysis method for hydroxyproline determination.

This work describes the development of a flow injection method to determine hydroxyproline (HYP), one of collagen's most abundant amino acids. Collagen is a protein with several applications and high nutritional value. Evaluating the feasibility of using collagen from fish skin over its mammalian source is essential. The determination of HYP requires the pre-treatment and hydrolysis of the fish skin to break down collagen into its amino acids, and the HYP value quantified relates to the collagen content. The determination was based on the HYP oxidation with permanganate in an alkaline medium and the consequent decrease of colour intensity registered. Under optimal conditions, the developed method enables the determination of the HYP within the dynamic range of 23.8 to 500 mg L-1, with a limit of detection (LOD) of 2.6 mg L-1 and a limit of quantification (LOQ) of 23.8 mg L-1. Different samples were processed, and the digests were analysed by the proposed method and with the conventional procedure with good correlation (relative error < 7%). Moreover, the analyte quantification is performed faster, simpler, and more accurately, with less toxic solutions. The reproducibility of the developed method was also evaluated by calculating the relative standard deviation of the calibration curve slope (RSD < 1%).

Hybrid Cerenkov-scintillation detector validation using Monte Carlo simulations

Objective. This study aimed at investigating through Monte Carlo simulations the limitations of a novel hybrid Cerenkov-scintillation detector and the associated method for irradiation angle measurements. Approach. Using Monte Carlo simulations, previous experimental irradiations of the hybrid detector with a linear accelerator were replicated to evaluate its general performances and limitations. Cerenkov angular calibration curves and irradiation angle measurements were then compared. Furthermore, the impact of the Cerenkov light energy dependency on the detector accuracy was investigated using the energy spectra of electrons travelling through the detector. Main results. Monte Carlo simulations were found to be in good agreement with experimental values. The irradiation angle absolute mean error was found to be less than what was obtained experimentally, with a maximum value of 1.12° for the 9 MeV beam. A 0.4% increase of the ratio of electrons having an energy below 1 MeV to the total electrons was found to impact the Cerenkov light intensity collected as a function of the incident angle. The effect of the Cerenkov intensity variation on the measured angle was determined to vary according to the slope of the angular calibration curve. While the contribution of scattered electrons with a lower energy affects the detector accuracy, the greatest discrepancies result from the limitations of the calculation method and the calibration curve itself. Significance. A precise knowledge of the limitations of the hybrid detector and the irradiation angle calculation method is crucial for a clinical implementation. Moreover, the simulations performed in this study also corroborate hypotheses made regarding the relations between multiple Cerenkov dependencies and observations from the experimental measurements.

Determination of trace vancomycin in edible animal tissues and assessment of matrix effects

Vancomycin (VCM) is known as the last line of defense against gram-positive bacteria. For one health, the rapid and effective monitoring of VCM is very important. In this study, a new liquid chromatography-tandem mass spectrometry method was established to detect VCM residues in livestock, poultry and fish. Tissues samples were extracted with 40% acetonitrile and 0.1% formic acid solution, and purified with the surface molecularly imprinted solid-phase extraction. The results showed that the method had good linearity (r > 0.99) in the range of 1–100 ng/mL, and the average recoveries of VCM in ten edible tissues at 1, 2 and 10 μg/kg spiking levels were 93.2–117%, with the relative standard deviations below 12.1%. The limits of detection and quantification were 0.5 and 1 μg/kg, respectively. Compared to conventional cartridges, the new cartridge could more effectively remove phospholipids in tissues samples. Furthermore, the statistical analysis demonstrated that there was a significant difference between the slopes of matrix-matched calibration curves of before and after purification (p < 0.05). The endogenous lysophosphatidylcholine proved to be a main effector that caused strong matrix inhibitory effect on VCM analysis.

ODP479 Equilibrium Dialysis ID-LC/MS/MS Procedure for Routine Measurement of Free Thyroxine in Serum

Abstract Free thyroxine (FT4) test is essential for diagnosis of thyroid diseases. Most FT4 tests used in patient care are immunoassays (IAs). However, concerns about the accuracy of FT4 IAs have been raised in the clinical laboratory community. Reference measurement procedure (RMP) for FT4 based on well-defined equilibrium dialysis (ED) of serum has been established and are well recognized. While FT4 RMP is highly accurate and precise, it is not intended for routine clinical use. Our aim is to develop an ED-based FT4 assay that is traceable to the RMP and suitable for routine measurements such as investigations in epidemiologic studies. The described assay is based on ED-LC-MS/MS. FT4 in serum was isolated from protein-bound T4 in serum according to the CLSI C45-A guideline. FT4 levels achieved equilibrium in a commercially available micro-ED plate after 18 hours. The dialysate was collected and spiked with internal standard (13 C 6 -T4). The IRMM-468 certified primary reference material (JRC, Belgium) of T4 was used for assay calibration. FT4 in dialysate was extracted with ISOLUTE-96-well C18 SPE plates (Biotage) before LC-MS/MS analysis. T4 could be resolved from Triiodothyronine (T3), reverse triiodothyronine (rT3), and other interferences in the dialysate on a C18 UPLC column with an elution time of less than 8 min. Selective reaction monitoring in positive electrospray ionization mode was used for detection. The measuring range covered 1-100 pg/mL of FT4. The assay sensitivity allowed detection of 0.5 pg/mL FT4, which is sufficient for detection of FT4 in normal and hypothyroid patient samples. The difference of this method to the CDC FT4 RMP was within ±5%. The imprecision of the routine assay, evaluated over four different days, was less than 10% CV. The slopes of calibration curves in dialysate matrix and water were comparable with each other indicating no significant matrix effect on FT4 quantification. The use of micro-ED plates in combination with an automated liquid handling system allows for effective automation of the procedure. The stability of T4 calibrator stock and working solutions were confirmed at various conditions. Currently, a comprehensive comparison study is underway between the newly developed routine method and the CDC FT4 RMP. The described routine FT4 assay can significantly improve throughput. The sensitivity, precision, and accuracy are suitable for routine FT4 measurements in clinical laboratories and conducting large epidemiologic studies. Applying this FT4 routine method to generate population data will support the use of standardized FT4 measurements and to address data needs on FT4 in general population. Presentation: No date and time listed