Optimal Sampling Time Research Articles

Hydroxyurea Pharmacokinetic Evaluation in Patients with Sickle Cell Disease

Background: Hydroxyurea (HU), also known as hydroxycarbamide, is an oral ribonucleotide reductase inhibitor. In 1999, the United States Food and Drug Administration (FDA) approved HU for the treatment of sickle cell disease (SCD). Since then, it has become the cornerstone in the management of SCD patients, helping to reduce vaso-occlusive crises, acute chest syndrome, the need for blood transfusions, hospitalizations and mortality. There is considerable variability among individuals in HU pharmacokinetic (Pk) parameters that can influence treatment efficacy and toxicity. The objective of this work is part of a clinical study aimed at investigating HU Pk and determining the optimal sampling time to estimate the Area Under the Curve (AUC) in SCD patients. Methods: HU plasma concentration in 80 patients at various time points (2, 4, 6, 24 h) following a 48-h drug washout was quantified using High-Pressure Liquid Chromatography (HPLC) coupled with an ultraviolet (UV) detection method previously described in the literature and adapted to new conditions with partial modifications. Results: The mean HU administered dose was 19.5 ± 5.1 mg/kg (range: 7.7–37.5 mg/kg). The median AUC quantified in plasma patients was 101.3 mg/L/h (Interquartile Range (IQR): 72.5–355.9) and it was not influenced by the weight-based dose. However, there was a strong positive correlation between AUC and Body Mass Index (BMI) as well as dose per Body Surface Area (BSA). Along with a three-point approach for AUC determination present in the literature, we show results obtained from a four-point sampling strategy, which is more useful and effective for better optimizing dose escalation to the maximum tolerated dose (MTD). Moreover, we observed that most patients achieved the maximum HU plasma concentration two hours after drug administration, regardless of age differences. Conclusions: HU treatment, which represents a milestone in the treatment of SCD due to its ability to reduce disease complications and improve patients’ quality of life, requires careful monitoring to optimize the individual dose for saving potential side effects and/or adverse events.

Online SPE-LC-MS-MS method for eight hydroxylated metabolites of polycyclic aromatic hydrocarbons in urine and determination of optimal sampling time after firefighter training

Polycyclic aromatic compounds (PAHs) are formed during incomplete combustion and firefighters are inadvertently at risk of being exposed to these and other hazardous compounds. Exposure to PAHs is often estimated by measuring their hydroxylated metabolites (OH-PAH) in urine. Here, an online-SPE LC-MS-MS method was set up for eight OH-PAHs thus increasing sample throughput and minimizing manual handling. The method was validated over a 5-month period and showed good reproducibility with intra- and inter-day variation of 2.4–8.1 % and 1.6–6.5 %, respectively, of low-level samples and accuracy (91.6–104.8 %) for a standard reference material. The method was applied to urine samples from conscripts training to become firefighters to determine the optimal sampling time for this training activity before a large intervention study. In total, six conscripts sampled urine 6–8 times over a 40-hr period during a 3-day training course. All eight metabolites were detected in ≥ 97 % of the samples and showed peak excretion 4–6 hrs after the training corresponding to 8–10 hrs after first exposure. Samples taken the morning after the exercise contained low levels of most metabolites. Consequently, 4–6 hrs post exposure is recommended as the optimal sampling time for quantification of PAH exposure and monitoring of potential differences in exposure.

Sampling time for different matrices in stress assessment of farmed Atlantic salmon post-smolt

The sustainability of commercial aquaculture production depends critically on prioritizing fish welfare management. Besides monitoring welfare parameters such as fish behaviour and water quality, fish stress level can also provide a reliable measure of the welfare status of farmed fish. Cortisol and 5 of its metabolites (5β-THF, cortisone, 5β-DHE, 5β-THE, β-cortolone) were previously identified by the authors as suitable stress biomarkers of farmed Atlantic salmon. Based on this knowledge, the present study aimed to investigate the time-related dynamics of these metabolites in plasma, skin mucus, bile and faeces over a 72 h- period. The objective was to determine the optimal sampling time for each matrix and to understand the clearance pathway of these metabolites following stress. An experiment was carried out using a total of 90 Atlantic salmon with an average weight of 438 (±132) g. The average sea temperature was 6.9 °C during the experimental period. A control group of 10 fish was first collected before the remaining 80 fish were submitted to a stress of netting and subsequent relocation into two separate cages. From each of these two stress groups, 10 fish were sampled at 1 h, 2 h, 4 h, 6 h and 12 h, 24 h, 48 h, 72 h after the stress event respectively. The concentrations of cortisol and its metabolites were measured at each of the sampling timepoint. The results demonstrated that plasma cortisol metabolites reached the highest concentration 4 h after stress and remained elevated despite the slight decrease for the remaining timepoints. The peak level was observed at 12 h post-stress in skin mucus and 24 h in bile and faeces. The findings suggest that these timepoints are the optimal for sampling Atlantic salmon post-smolt following stressful events in acute stress studies. Furthermore, the results reveal that analysing cortisol and its metabolites, both in free and conjugated forms, rather than free cortisol provides greater flexibility as their concentrations are less affected by sampling procedure. This study confirms the appropriateness of skin mucus and faeces as less-invasive sample matrices for fish stress evaluation and provides a basis for further developing low invasive tools for monitoring the welfare of farmed salmonid.

Response patterns of moss to atmospheric nitrogen deposition and nitrogen saturation in an urban–agro–forest transition

Abstract. Increasing trends of atmospheric nitrogen (N) deposition resulting from a large number of anthropogenic emissions of reactive N are dramatically altering the global biogeochemical cycle of N. Nitrogen uptake by mosses occurs mainly from the atmosphere, making it a competent bio-indicator of N deposition. However, high uncertainties exist when using mosses to indicate N deposition, especially in choosing sampling periods and sampling frequencies. In this study, atmospheric N deposition and moss N content in the urban–agro–forest transition, a region with a high N deposition level of 27.46–43.70 kg N hm−2 yr−1, were monitored, and the method for monitoring atmospheric N deposition by mosses was optimized. We found that the optimal sampling frequency is within 6 months per time, and the optimal sampling times are winter (January and February), autumn (October and November), and summer (July and August), which provides us with a more accurate estimation of atmospheric N deposition than other scenarios. In addition, the moss N content serves as a more reliable N species. This study eventually allowed mosses to be used more effectively and sensibly as an indicator of atmospheric N deposition and helped to improve the accuracy of the model for quantifying N deposition.

Postsurgical utility of copeptin for the prediction of postoperative arginine vasopressin deficiency.

Arginine vasopressin deficiency (AVD) following neurosurgical procedures for pituitary disorders is common and can delay discharge. Copeptin, a stable surrogate marker of arginine vasopressin, may predict postoperative AVD. The authors' aim was to assess the optimal postoperative sampling time and cut-point concentration of copeptin to predict the development of postsurgical AVD. Adults without preexisting AVD who were undergoing surgery for a pituitary lesion between February 2020 and April 2022 were eligible for study inclusion. Two samples were drawn from each patient postoperatively to assess the copeptin concentration using an immunofluorescent assay. Samples were denoted as "early" (within 6 hours of extubation) or "postoperative day 1" (POD1; within 10-30 hours of extubation). Patients were evaluated for the development of AVD. One hundred ninety-two patients (54.2% female) with a median age of 54.5 years (IQR 39.8-67.0 years) were included in the study. The median copeptin concentration at both time points was significantly lower in those with AVD (transient or permanent; n = 22, 11.5%) than in those without (early: 4.9 vs 18.7 pmol/L, p < 0.001; POD1: 3.4 vs 4.9 pmol/L, p < 0.001) but did not differ in those who developed transient versus permanent AVD. The optimal copeptin cut point for the prediction of AVD was < 8.5 pmol/L for early samples (sensitivity 0.70, specificity 0.80, positive predictive value [PPV] 0.29, negative predictive value [NPV] 0.96) and < 4.3 pmol/L for POD1 samples (sensitivity 0.82, specificity 0.63, PPV 0.22, NPV 0.96). In early samples, a copeptin cutoff of 22.9 pmol/L increased the sensitivity for the detection of AVD to 95% with an NPV of 99%. The proportion of patients who had AVD was higher (60.0% vs 8.8%, p < 0.001) and the copeptin concentration lower (early: 4.3 vs 17.0 pmol/L, p < 0.001; POD1: 2.7 vs 4.9 pmol/L, p < 0.001) among those who had undergone surgery for a craniopharyngeal duct pathology versus a pituitary adenoma. Although copeptin was lower in patients with persistent Cushing's disease than in those in remission, the difference did not reach statistical significance (early p = 0.11, POD1 p = 0.52). Furthermore, the copeptin concentration could not predict the development of syndrome of inappropriate secretion of antidiuretic hormone. Patients without AVD who had received stress dose steroids intraoperatively had lower median early copeptin (11.7 vs 19.1 pmol/L, p = 0.027). In early postoperative copeptin samples, the optimal copeptin cut point for AVD diagnosis was < 8.5 pmol/L, and a level > 22.9 pmol/L had predicative utility in excluding AVD. Caution should be used when interpreting copeptin results, as patients administered glucocorticoids intraoperatively without AVD had lower median copeptin concentrations.

Inkjet-printed MOS-based MEMS sensor array combined with one-dimensional convolutional neural network algorithm for identifying indoor harmful gases

To achieve a highly accurate and efficient analysis of mixed gases, it is crucial to develop an electronic nose system with high sensitivity of gas sensors and low data processing complexity. In this study, the metal oxide semiconductor (MOS) based micro-electromechanical system (MEMS) gas sensor array was prepared by inkjet printing sensing materials onto a micro-hotplate. The pattern recognition unit employed a one-dimensional convolutional neural network (1D-CNN) to identify 7 types of gases. While the optimal traditional machine learning algorithm achieved an 80% recognition accuracy, the 1D-CNN can achieve 99.8%. Furthermore, the impact of varying time series input lengths on the model accuracy was investigated, pinpointing an optimal sampling time of 15 s. This work showed that integrating the MEMS sensor array with the 1D-CNN algorithm might offer a promising approach for intricate gas classification and identification.

Head-to-Head Comparison of Novel Vaccine Technologies Comes with a Minefield of Challenges.

Modern vaccine development is having a golden period, with a variety of novel subunit technologies being introduced into clinical development in recent years. This opens the opportunity to find the best platform to use for novel vaccine antigen candidates through head-to-head comparative studies. Seldom appreciated is, however, the fact that these different technologies often do not have the same optimal antigen dose ratio, prime-boost regime and peak timepoint for measuring immunity. Instead, the preclinical studies that make the basis for platform selection use standard protocols not optimized for individual vaccines and fail to make selection on an informed basis. Here, I discuss the opportunities we have to optimize vaccine platform technologies through a better understanding of vaccine priming kinetics, the optimal antigen dose and sampling time and location.

Use of the Subcutaneous Triptorelin Stimulation Test for Diagnosis of Central Precocious Puberty.

The gold standard gonadotropin-releasing hormone (GnRH) stimulation test uses the response to intravenously injected gonadorelin to diagnose central precocious puberty (CPP). However, gonadorelin is not always readily available. This study investigated the diagnostic efficacy of the subcutaneous triptorelin test and the optimal blood sampling time for diagnosis of CPP. This study retrospectively examined the medical records of 220 girls who had undergone either the triptorelin or gonadorelin test and compared their clinical characteristics. We retrospectively compared clinical parameters between girls diagnosed with CPP (n = 111) and idiopathic premature thelarche (IPT) (n = 109) using three different diagnostic methods: the gonadorelin, triptorelin 120 min, and triptorelin 180 min tests. The diagnostic ability of the stimulated luteinizing hormone (LH) concentration in the triptorelin test for CPP was evaluated using receiver operating characteristic (ROC) analysis. The CPP group exhibited higher basal and peak gonadotropin levels, more advanced bone age, and a lower body mass index standard deviation score than the IPT group. In the gonadorelin test group, all girls with CPP exhibited a peak LH response 30-60 min after intravenous gonadorelin injection. In the triptorelin test group, most girls with CPP exhibited a peak LH response 60-180 min after subcutaneous triptorelin injection (n = 68). On the ROC curve, a peak LH concentration of ≥ 4.52 IU/L at 120 min had the highest CPP diagnostic accuracy, with sensitivity and specificity of 100% and 95.83%, respectively.

Design Evaluation and Optimization of Population Pharmacokinetics Model Using an R Package PopED

The rising cost in drug development has led to continuous calls for more efficient and powerful design optimization and analysis tools for pkpd studies. More sophisticated models are increasingly used to reflect reality, and current models invariably include non-linear mixed effects models that frequently require specialized computational tools for the design and analysis of the study. Population PK analysis employs non-linear mixed effects models and evaluates designs and optimizes them via a specialized yet versatile software package called PopED (version 0.6.0) in programming language R (version 4.2.2) for pharmacometrics analyses. We demonstrate the utilities of the package when different models and statistical criteria are used in real settings to determine the optimal sampling times and optimal dose levels for the subjects. We provide two applications; the first is illustrative and the second is a new application on developing an optimal dosing scheme for a two-compartment PK model with perturbation. Our target audiences are mathematicians and statisticians who are not aware of this useful and powerful analytic tool.

THU114 Postsurgical Use Of Copeptin In The Prediction Of Postoperative Arginine Vasopressin Deficiency

Abstract Disclosure: D.Z. Erickson: None. D. Donegan: None. J. Van Gompel: None. J. Atkinson: None. M. Link: None. F. Meyer: None. M. Peris-Celda: None. G. Spears: None. J. Bornhorst: None. M. Hoplin: None. Dysnatremias are common after neurosurgical procedures. Depending on the cohort assessed, transient arginine vasopressin deficiency (AVD) following neurological procedures is seen in up to 46% of patients which can delay discharge. Copeptin (COPEP), a stable surrogate marker of arginine vasopressin, has demonstrated utility in the prediction of postoperative AVD, however COPEP cutoff and sample timing has varied. Aim: To assess the optimal sampling time and cut point concentration of COPEP to predict the development of post-surgical AVD. Method: Adults who had transsphenoidal surgery (TSS) for a sellar or suprasellar mass between February 2020 and April 2022 without pre-existing AVD were prospectively enrolled if agreeable. Two COPEP samples (immunofluorescent assay on B.R.A.H.M.S Kryptor Compact PLUS) included “early” sample 1-6 hours following extubation, and another post-op day 1 (POD1, 10-30 hours of extubation). Patients were assessed for the development of AVD; defined as new onset hypotonic (&amp;lt; 295 mmol/kg) polyuria (&amp;gt;50 ml/kg/d) without other causes. Patient demographics and tumor characteristics were collected. Results: 192 patients (median age 54.5 (39.8-67.0) years with 54.2% female) were included. Surgical indications included non-functioning pituitary adenoma (N=101), functioning pituitary adenoma (N= 78), disorders or the craniopharyngeal duct (N=10) and other (N=3). Median COPEP levels were associated with age, but not sex. Median COPEP levels were significantly lower at both time points in patients who developed AVD (N=20, 10.4%) vs those who did not, (early: 4.9 vs 18.7 pmol/L, P= &amp;lt;0.001; POD1: 3.35 vs 4.9 pmol/L, P=&amp;lt;0.001). Change in median COPEP level between the 2 sample times was lower in those who developed AVD -1.8 pmol/L vs who did not -12.6 pmol/L (P&amp;lt;0.001). ROC curve analysis of early COPEP indicated that a level &amp;gt;20.3 pmol/L had a negative predictive value (NPV) of 97% whereas POD1 level &amp;gt;6.7 pmolL had a NPV of 96%. In univariate logistic analysis, lower early COPEP was associated with higher risk of AVD (OR=0.34, CI 0.26 -0.62, p=0.008), with an optimal cut point of 8.5 pmol/L. A similar association was seen for POD1 COPEP (OR=0.19, CI 0.07- 0.53, p= 0.002), which had an optimal cut point of 4.3 pmol/L. In patients with disorders of the craniopharyngeal system vs those who had TSS for other reasons, AVD was more common (60% vs 9%, P&amp;lt;0.001) and median COPEP levels were lower at both time points. Those without AVD who received stress dose steroids intraoperatively had lower median early COPEP (11.7 vs 19.1 pmol/L, P=0.27). Conclusion: In early samples taken following extubation, the optimal COPEP cut point for AVD diagnosis was 8.5 pmol/L and a level of &amp;gt;20.3 pmol/L has predicative utility in excluding AVD. However, caution should be used in patients who are administered glucocorticoids intra-operatively as this was associated with a lower median COPEP level. Presentation: Thursday, June 15, 2023

Algorithm for monitoring patients after tick bite in the context of Lyme-borreliosis

Timely diagnosis of Lyme-borreliosis (LB) is the key to its successful treatment. Outpatient monitoring of patients after tick bite based on the algorithm is able to optimize the early diagnosis of LB, shorten the start of treatment and improve the disease surveillance.Purpose. Creation of an algorithm for monitoring patients after tick bite for use in outpatient settings by primary care physicians. Material and methods. A retrospective, non-randomized, single-center cohort study was conducted based on the analysis of data from 660 outpatient records of patients consulted by an infectious disease specialist in the Infectious clinical hospital No.1 in Moscow. Patients were divided by age and the presence or absence of a diagnosis of LB. Confirmation of the diagnosis was carried out according to clinical and/or laboratory criteria using methods of enzyme-linked immunoassay and immune blot. Results. The analysis of the results of enzyme immunoassay of antibodies to borrelia in patients with LB was carried out. The optimal sampling time was 7 or more weeks from the moment of tick bite and 4 or more weeks from the moment of onset of symptoms. The specificity of immunological diagnostics in patients with excluded LB was evaluated. The proportion of doubtful and false positive results in such patients was high — 28.1%. False positive results were more common in adults (37.6%) compared with children (9.8%), which is associated with more frequent false positive results of IgM determination (34.1% in adults, 4.9% in children). Based on the data of our study, an algorithm for monitoring patients after tick bite has been developed, focused on use in outpatient settings by primary care physicians.

RNA sampling time on postmortem avian carcasses in the wild

Genetic sampling, especially high‐quality RNA from wild avian populations, is challenging in wildlife biology due to rapid RNA degradation. Although carcasses could be a potential RNA source, the optimal postmortem sampling time on the avian carcasses under field conditions remains unclear. Here, we carried out a field experiment on the Qinghai‐Tibet Plateau (QTP) and evaluated the relationship between PMI and RNA degradation in three tissue types (muscle, brain, and liver) of the domestic chicken Gallus gallus domesticus carcasses. In the muscle and brain tissues, we found that the RNA Integrity Number (RIN) of samples collected within 60 h postmortem was more than 7.0, suggesting a high RNA extract quality. The following RNA‐seq experiment demonstrated that gene expression profiles of the samples collected within 36 h postmortem were comparable to those of fresh samples (i.e. 0 h), with a low percentage of differentially expressed genes (&lt; 3.0%) observed between samples at 0 and 36 h postmortem. However, in the liver tissue, RNA samples already degraded at 12 h postmortem, showing low RIN values (&lt; 7.0), different gene expression profiles from fresh samples, and a high percentage of differentially expressed genes (15.6%). Therefore, our study suggests that samples from muscle and brain tissues collected within 36 h postmortem are qualified for RNA‐seq analyses. In contrast, only the fresh RNA samples from liver tissue are qualified. Our study provides a practicable and efficient sampling strategy for the transcriptome study on avian populations under extreme environment such as the QTP.

The clinical application value of salivary pepsin in the diagnosis of gastroesophageal reflux diseases.

Peptest is a noninvasive and convenient diagnostic kit for gastroesophageal reflux disease (GERD). We aimed to explore the application value of Peptest in the diagnosis of GERD. Patients suspected of GERD all completed 24 h pH-impedance monitoring (24 h MII-pH) and then took proton pump inhibitor (PPI) 2 weeks. The postprandial, post-symptom and random salivary samples were taken. Receiver operating characteristic analysis was used to identify the best cutoff value of Peptest, to differentiate GERD patients from non-GERD patients and the optimal sampling time of Peptest was analyzed. Reflux characteristics and esophageal motility between Peptest (+) group and Peptest (-) group were compared in negative 24 h MII-pH patients. Peptest concentration were compared among non-reflux, distal reflux, and proximal reflux groups according to 24 h MII-pH curve. The area under the curve of post-symptom Peptest was highest in three time points and the diagnostic specificity was 81.0% and sensitivity was 53.3% with the diagnostic value of 86 ng/mL. Compared with negative Peptest group, distal mean nocturnal baseline impedance was significantly lower, gastroesophageal junction contractile integral was substantially lower in positive Peptest group in negative 24 h MII-pH patients. The concentration of post-symptom and postprandial Peptest increased gradually in the non-reflux, distal reflux, and proximal reflux groups. Peptest has a relatively low diagnostic value for GERD. Post-symptom Peptset is the best sampling time with the optimal value of 86 ng/mL and may have auxiliary diagnostic value for negative 24 h MII-pH patients. Peptest may assist 24 h MII-pH in monitoring proximal reflux.

Effects of parental genotypes on embryo rescue of seedless grape hybrid

ABSTRACT The success of seedless grape embryo rescue depends on many factors. To study the effects of parental genotypes on embryo rescue, we conducted 11 hybridisation combinations using nine stenospermocarpic seedless grapes as female parents and three seedless or seeded grapes as male parents. At the optimal sampling time of each mother plant, the hybrid ovules were inoculated and cultured on a solid–liquid biphasic MM3 medium. Then, the bare embryos were removed and inoculated on a WPM medium for germination and seedling formation. The results showed that when ‘Jupiter’ (seedless) was the male parent, ‘Perlette’ had the highest rates of embryo development, germination and seedling formation, followed by ‘Kunxiang Seedless’; when ‘Su-67’ (seedless) was the male parent, ‘FZ42’ had the highest embryo development rate; when ‘Beichun’ (seeded) was the male parent, ‘Fresno Seedless’ had the best embryo rescue results, followed by ‘Qinhong No.10’. These suggest that ‘Perlette’, ‘Kunxiang Seedless’, ‘Fresno Seedless’ and ‘Qinhong No.10’ are suitable female parents for embryo rescue. When ‘FZ42’ was the female parent, ‘Su-67’ was better than ‘Jupiter’ as the male parent; when ‘Perlette’ was the female parent, ‘Jupiter’ and ‘Su-67’ as male parents had no significant difference, indicating that paternal genotype has a certain effect on embryo rescue. HIGHLIGHTS The maternal genotype has a significant effect on the embryo rescue of seedless grapes. The paternal genotype has a certain effect on embryo rescue of seedless grapes. ‘Perlette’, ‘Kunxiang Seedless’, ‘Fresno Seedless’ and ‘Qinhong No.10’ are suitable female parents. A total of 345 hybrids from 11 cross-combinations were obtained by embryo rescue.

Model predictive control with exogenous auto-regressive model to improve performance in the CO2 removal

Model predictive control (MPC) is used in the CO2 removal process in the Subang field to improve its control performance. MPC is used to maintain the CO2 concentration at the sweet gas output by controlling the feed gas pressure (PIC-1101), makeup water flow rate (FIC-1102), and amine flow rate (FIC-1103). The empirical model applied to MPC to represent the process model is the auto-regressive exogenous (ARX) model. The ARX model is compared with the first order plus dead time (FOPDT) model based on the root mean square error (RMSE) between the model and the actual process, then MPC parameters are tuned which include sampling time (T), prediction horizon (P) and control horizon (M) to control for the three variables. Improved control performance is measured based on the integral square error (ISE). The results show that the ARX model is the best model for the CO2 removal process with an RMSE value of 35%-91% smaller than the FOPDT model. The optimal control parameters Prediction Horizon (P), Control Horizon (M) and Sampling Time (T) in the CO2 removal process are 75, 25 and 1 on PIC-1101, 25, 10 and 1 on FIC-1102, and 30, 25 and 1 on FIC-1103. The MPC-ARX (MPC using ARX model) can improve the control performance of 33% in the servo control and 6-56% on the regulatory control. However, not all of them showed an increase in control performance improvement from previous studies even though they had used the best model (ARX). This is due to the MPC parameter setting that is not yet appropriate, so it needs to be retuning.

Optimizing Vancomycin Therapy in Critically Ill Children: A Population Pharmacokinetics Study to Inform Vancomycin Area under the Curve Estimation Using Novel Biomarkers.

Area under the curve (AUC)-directed vancomycin therapy is recommended, but Bayesian AUC estimation in critically ill children is difficult due to inadequate methods for estimating kidney function. We prospectively enrolled 50 critically ill children receiving IV vancomycin for suspected infection and divided them into model training (n = 30) and testing (n = 20) groups. We performed nonparametric population PK modeling in the training group using Pmetrics, evaluating novel urinary and plasma kidney biomarkers as covariates on vancomycin clearance. In this group, a two-compartment model best described the data. During covariate testing, cystatin C-based estimated glomerular filtration rate (eGFR) and urinary neutrophil gelatinase-associated lipocalin (NGAL; full model) improved model likelihood when included as covariates on clearance. We then used multiple-model optimization to define the optimal sampling times to estimate AUC24 for each subject in the model testing group and compared the Bayesian posterior AUC24 to AUC24 calculated using noncompartmental analysis from all measured concentrations for each subject. Our full model provided accurate and precise estimates of vancomycin AUC (bias 2.3%, imprecision 6.2%). However, AUC prediction was similar when using reduced models with only cystatin C-based eGFR (bias 1.8%, imprecision 7.0%) or creatinine-based eGFR (bias -2.4%, imprecision 6.2%) as covariates on clearance. All three model(s) facilitated accurate and precise estimation of vancomycin AUC in critically ill children.

Estimation of evaporator valve sizes in supermarket refrigeration cabinets

In many applications, e.g. fault diagnostics and optimized control of supermarket refrigeration systems, it is important to determine the heat demand of the cabinets. This can easily be achieved by measuring the mass flow through each cabinet, however that is expensive and not feasible in large-scale deployments. Therefore it is important to be able to estimate the valve sizes from the monitoring data, which is typically measured. The valve size is measured by an area, which can be used to calculate mass flow through the valve — this estimated value is referred to as the valve constant. A novel method for estimating the cabinet evaporator valve constants is proposed in the present paper. It is demonstrated using monitoring data from a refrigeration system in a supermarket in Otterup (Denmark), consisting of data sampled at a one-minute sampling rate, however it is shown that a sampling time of around 10–20 min is adequate for the method. Through thermodynamic analysis of a two stage CO2 refrigeration system, a linear regression model for estimating valve constants is developed using time series data. The linear regression requires that transient dynamics are not present in the data, which depends on multiple factors e.g. the sampling time. If dynamics are not modelled it can be detected by a significant auto-correlation of the residuals. In order to include the dynamics in the model, an Auto-Regressive Moving Average model with eXogenous variables (ARMAX) is applied, and it is shown how it effectively eliminates the auto-correlation and provides less bias and higher accuracy of the estimates. Furthermore, it is shown that the sample time has a huge impact on the estimates. Thus, a method for selecting the optimal sampling time is introduced. It works individually for each of the evaporators, by exploring their respective frequency spectrum. That way, a reliable estimate of the actual valve constant can be achieved for each evaporator in the system and it is shown that sampling times above 10 min are optimal for the analysed systems.

A Two-Step E-Nose System for Vehicle Drunk Driving Rapid Detection

With the rapid development of shared cars, to reduce the phenomenon of drunk driving in shared cars, we have studied the onboard drunk driving rapid detection electronic nose system suitable for shared cars. To accurately judge whether the driver is drunk while driving in the presence of interfering gases such as passenger exhalation and the volatile smell containing alcohol, this paper proposes a two-step drunk driving detection frame for shared cars that first judges whether someone in the car is drunk and then judges whether the driver is drunk. To reduce the cost and volume of the electronic nose, the sensor array was optimized based on the random forest algorithm. To find the optimal sampling time, we processed the original data by time slicing. Finally, using the two-step framework proposed by us, the accuracy of the first step and the second step of driver drunk driving detection reached 99.44% and 100%, respectively, with a sampling time of 5 s. After algorithm optimization, only 9 of the 21 sensors were left. This paper presents a practical electronic nose system for the detection of drunk driving in shared cars.

Copeptin Reflect Left Ventricular Systolic Function at Early Stage of Acute Myocardial Infarction in a Pig Model.

Measurement of biomarkers early after acute myocardial infarction (AMI) might provide a cost-effective and widely available tool to assess infarct severity, myocardial dysfunction, and clinical outcomes. We aimed to induce AMI in miniature pigs, measure the levels of serum biomarkers and global LV function dynamically and explore the release kinetics and optimal sampling time points of copeptin and its correlation with global LV function. We induced AMI in the experimental group using a closed-chest model. Left ventricular (LV) function was detected by dual-source computed tomography (DSCT) and serum copeptin was determined by ELISA. The serum copeptin levels were increased at 1 hour, peaked at 3 hours, gradually decreased after 6 hours, and returned to baseline 3 days after AMI. At 3 to 6 hours, the copeptin cutoff of 16.97 to 17.44 pmol/l had 100% sensitivity and 100% specificity (P ⩽ .001) for AMI. Serum copeptin levels at 3 hours and 3 days were negatively correlated with the 3-hours LVEF (P ⩽ .001), respectively. Serum copeptin levels change in time, and measurements at 3 to 6 hours after AMI had the highest predictive value.

Seasonal and Soil Use Dependent Variability of Physical and Hydraulic Properties: An Assessment under Minimum Tillage and No-Tillage in a Long-Term Experiment in Southern Italy

Defining the optimal sampling time across the growing season is crucial to standardize sampling protocols for soil physical status monitoring and to achieve comparable results under different experimental conditions and on different sites. In this study, the seasonal variability of soil physical and hydraulic properties under two conservative soil management strategies, minimum tillage and no-tillage, was evaluated in a long-term field experiment. On two sampling dates, autumn 2021 and summer 2022, soil bulk density (BD) and volumetric soil water content at the time of the experiments (θi) were measured in each experimental unit and Beerkan infiltration experiments were performed. The soil water retention curve and the hydraulic conductivity function were then estimated using the Beerkan estimation of soil transfer parameters (BEST) methodology. In this way, the saturated hydraulic conductivity (Ks) and a set of capacitive indicators—plant available water capacity (PAWC), soil macroporosity (PMAC), air capacity (AC) and relative field capacity (RFC)—were obtained. Results underlined the role of soil moisture conditions as a main factor affecting variability in soil physical properties. Different soil moisture under autumn and summer samplings significantly affected BD (1.0093 and 1.1905 g cm−3, respectively, in autumn and summer) and Ks (0.0431 and 0.0492 mm s−1). Relationships observed between BEST-derived variables, such as PMAC (or AC) and RFC, and measured variables, such as BD, showed consistent results, with increases in PMAC to BD decreases. However, a comparison of capacity-based indicators obtained by BEST with those obtained from measured soil water retention curves, in a previous year but under comparable soil conditions, highlighted some discrepancies. This finding drives the focus towards the need to use more robust datasets deriving from experimental measurements or from coupling information obtained from measured and estimated data. Finally, this study provided further evidence that, in the long-term field experiment investigated, the two soil management systems allowed keeping the values of key soil physical quality indicators, such as bulk density and saturated hydraulic conductivity, within the optimal or near- optimal reference ranges.