Acceptable Level Of Precision Research Articles

Various techniques for resolving overlapping ultraviolet spectra of combination pharmaceutical dosage forms containing hydroxychloroquine and paracetamol

Ten novel spectrophotometric approaches were developed for the initial examination of the Hydroxychloroquine and Paracetamol medications. These procedures are straightforward, specific, easy to use, and provide exact and accurate results. The determination was conducted through the utilization of several approaches, including zero order (dual wavelength, zero crossing, advanced absorption subtraction and spectrum subtraction), derivative (first derivative of zero crossing), ratio (ratio difference, ratio derivative) and mathematical (bivariate, simultaneous equation, and Q-absorbance) techniques. After undergoing validation in accordance with ICH criteria, it was established that each of these methods achieved acceptable levels of precision, repeatability, robustness, and accuracy. The advantages and disadvantages of each method are demonstrated, and the proposed and reported methodologies were statistically compared.Graphical

Analysis of road construction waste generation in developing economies: A focus on surfacing and sub-base construction projects in Sri Lanka

The motivation for this study was to develop simplified tools to estimate material wastage during road construction projects. In developing countries, there is a lack of information about material wastage factors (MWFs) in road construction projects. The purpose of this study is to reveal the MWFs of materials used in road construction. To investigate MWFs, statistics were collected from a sample of 58 road contracts concluded in the southern province of Sri Lanka, comprising 245 road construction projects. Of the selected sample, 80% of the road projects utilized wearing course (asphalt concrete), aggregate base course (ABC), cationic slow setting emulsion 1 (CSS1) and sand. The mean MWFs were calculated only for ABC, wearing course and CSS1 as 8.69%, 5.21% and 6.8%, respectively, because the authors could only achieve acceptable precision levels for these three types of materials. The coefficient of variation (CV) for all these three types of materials ranged from 25% to 3%. Based on collected data, this study proposes equations to predict waste generation for CSS1 and wearing course. Implementing the derived equations to predict waste generation can aid in efficient planning and help construction companies to move towards more sustainable practices.

Development and Evaluation of a Hybrid Measurement System to Determine the Kinematics of the Wrist.

Optical Motion Capture Systems (OMCSs) are considered the gold standard for kinematic measurement of human movements. However, in situations such as measuring wrist kinematics during a hairdressing activity, markers can be obscured, resulting in a loss of data. Other measurement methods based on non-optical data can be considered, such as magneto-inertial measurement units (MIMUs). Their accuracy is generally lower than that of an OMCS. In this context, it may be worth considering a hybrid system [MIMU + OMCS] to take advantage of OMCS accuracy while limiting occultation problems. The aim of this work was (1) to propose a methodology for coupling a low-cost MIMU (BNO055) to an OMCS in order to evaluate wrist kinematics, and then (2) to evaluate the accuracy of this hybrid system [MIMU + OMCS] during a simple hairdressing gesture. During hair cutting gestures, the root mean square error compared with the OMCS was 4.53° (1.45°) for flexion/extension, 5.07° (1.30°) for adduction/abduction, and 3.65° (1.19°) for pronation/supination. During combing gestures, they were significantly higher, but remained below 10°. In conclusion, this system allows for maintaining wrist kinematics in case of the loss of hand markers while preserving an acceptable level of precision (<10°) for ergonomic measurement or entertainment purposes.

Optimizing solid phase extraction and HPLC-MS/MS parameters for reliable quantification of COVID-19 pharmaceuticals in Mexico City’s wastewater: A design of experiments approach

Through the COVID-19 health crisis, a plethora of new medications, along with some discontinued pharmaceuticals, were directly tested on population to assess their efficacy in symptom management. Consequently, residues from these treatments were systematically disposed into sewage systems, presenting a novel contamination challenge in urban centers. To effectively address this issue by environmental authorities, the presence of these pollutants in wastewater must be accurately quantified. Herein, we conducted a meticulous study to validate an analytical method based on solid-phase extraction (SPE) and high-performance liquid chromatography coupled with tandem mass spectrometry (HPLC-MS/MS) to detect six pharmaceuticals (metformin, famotidine, indomethacin, dexamethasone, azithromycin, and ivermectin) in wastewater. Using a Plackett-Burman design (PBD), the eight parameters significantly impacting on the HPLC-MS/MS technique were established based on the analytical signal of the six analytes. Subsequently, in conjunction with a Box-Behnken design (BBD), optimal analysis conditions were determined as follows: injection volume: 10 µL, column temperature: 20 °C, capillary voltage: 4100 V, drying gas temperature and flow rate of 350 °C and 7 L min−1 respectively, nebulizer pressure: 15 psi, concentration of formic acid and ammonium acetate in the mobile phase of 0.1 % and 10 mmol/L, respectively. SPE was optimized through a univariable experimental design. OASIS HLB cartridges exhibited the highest extraction efficiency compared to highly polar and non-polar adsorbents. The optimal sample loading conditions were set as 250.0 mL of water sample at pH = 9.0. The washing conditions were 5.0 mL of a 95:5 water:methanol solution, while elution conditions were optimal using 6.0 mL of a 98:2 methanol:formic acid solution. After evaporating the eluate to dryness and reconstituting in 1.0 mL of a 98:2 methanol:formic acid solution, a concentration factor of 250 was achieved. The analytical method was validated using for matrices, namely, raw and treated wastewater, wastewater percolated through soil and groundwater. Acceptable levels of precision and accuracy were achieved for all analytes in the tested matrices. Using the validated method, the six pharmaceuticals were quantified in environmental samples, revealing high levels of metformin, dexamethasone, and azithromycin in Mexico City’s sewage. Highly polar compounds displayed mobility through environment as they were present in effluent samples, percolated wastewater, and groundwater.

The Precision of Lumbar Spine BMD and TBS on Different Vertebral Combinations

OBJECTIVE The objective of this study is to compute the precision and LSC of BMD and TBS at the lumbar spine using dual-energy X-ray absorptiometry in different vertebral combinations. METHODS Thirty female participants (age 58.8 ± 4.0 years, height: 155.0 ± 5.2 cm, weight: 57.4 ± 8.6 kg and BMI: 23.9 ± 3.6) were scanned at the lumbar spine twice in the same day using DXA. The precision and LSC of BMD and TBS were computed in terms of the RMS-SD and %CV using the ISCD Advanced Precision Calculation Tool. RESULTS The precision and LSC of BMD of the 4 vertebrae combinations showed the best precision and also showed a similar trend (0.005 g/cm2 and 0.62%, 0.013 g/cm2 and 1.71%), respectively. For TBS, the precision and LSC followed a similar pattern as BMD but was inferior to those of BMD. The %CV LSC of BMD for all vertebrae combinations did not exceed 5.3% as recommended by ISCD (15). The %CV LSC of TBS for 2-4 vertebrae combinations were within 5.8% with the exception of the individual vertebra which was unacceptable (%CV range 6.17-8.98). CONCLUSIONS All vertebrae combinations had an acceptable level of precision and LSC for BMD monitoring. However, the precision and LSC of TBS were inferior to those of BMD, and individual vertebra were not appropriate for TBS monitoring. KEYWORDS precision, least significant change (LSC), bone mineral density (BMD), trabecular bone score (TBS)

Coronado CLL: A Phase Ib/II Trial of Combination Rp-3500 and Olaparib in DNA Damage Repair Pathway Deficient Relapsed/Refract ory Chronic Lymphocytic Leukemia

Background: Genes within the DNA damage repair ( DDR) pathways are frequently mutated in relapsed/refractory ( R/R) chronic lymphocytic leukemia ( CLL) and clinically correlate with decreased response rates and shortened progression-free ( PFS) and overall survivals ( OS). The most commonly affected DDR genetic aberrations include deletion 17p13 [ del(17p)], deletion 11q22.3 [ del(11q)], and mutations in TP53, ATM, SF3B1, XPO1 and POT1. Due to their poor clinical outcomes, patients (pts) with DDR-deficient CLL remain an area of unmet need and the development of novel drugs and combinations will be critical to improving their prognosis. Mechanistically, CLL cells with DDR genetic alterations lack double-stranded DNA breakage repair and major cell cycle checkpoint pathways. Therefore, R/R CLL cells are dependent on single-stranded DNA breakage ( SSB) repair and alternative DNA replication arrest machinery to ensure DNA integrity, strand repair and cell survival. DNA damage at the replication fork is primarily recognized by ataxia telangiectasia and rad3 ( ATR) protein, which ensures mitotic arrest and recruitment of poly (ADP-ribose) polymerase ( PARP) based SSB repair mechanisms. In germline DDR-deficient breast and ovarian cancers with BRCA1/BRCA2 mutations, the use of both single agent PARP inhibitors ( PARPi) and ATR inhibitors ( ATRi) have led to significant disease response and improved OS. Furthermore, combination PARPi and ATRi have demonstrated synergistic activity in preclinical data producing increased apoptosis and cell death in BRCA2-mutated ovarian cell lines. In DDR-deficient CLL primary cell and murine models, single agent PARPi and ATRi have demonstrated significant cell death as compared to wildtype CLL and healthy donor lymphocytes. RP-3500 is a highly potent ATRi. In preclinical data generated in SUM149PT DDR-deficient breast cancer cell lines, combining RP-3500 with the PARPi, olaparib, substantially reduced tumor volume at lower doses than the previously determined maximum tolerated dose ( MTD) of each drug when used as monotherapy. Furthermore, intermittent dosing of both drugs (3 days per week) demonstrated equal cell apoptosis as continuous dosing. Therefore, we hypothesize that the combination of RP-3500 and olaparib will be a highly efficacious treatment for R/R DDR-deficient CLL pts and that the lower dosages and intermittent dosing schedule required of each drug when administered in combination will improve safety of the treatment. Study Design and Methods: This is a multi-site (University of Utah and the Ohio State University), phase Ib/II investigator-initiated clinical trial using combination RP-3500 and olaparib in R/R CLL pts with DDR pathway deficiencies to determine the safety and efficacy of the drug combination (NCT05405309). Primary objectives include determining the MTD in phase Ib leading to the recommended phase 2 dose ( RP2D), and overall response rate ( ORR) in phase II. Key secondary objectives include safety and tolerability, PFS, OS and duration of response of the combination. Eligibility: Key inclusion criteria include a diagnosis of CLL according to the 2018 iwCLL guidelines, age ≥18 years, ECOG performance status of ≤2, R/R after at least 2 prior lines of therapy. Primary CLL cells must exhibit any one of the following abnormalities: a) somatic mutation(s) in TP53, ATM, SF3B1, XPO1 or POT1, or b) positive FISH for either del(17p) or del(11q). Statistical Methods: Phase Ib: The phase Ib of the trial will utilizea keyboard design, which is a novel Bayesian method that typically underestimates the MTD. The target toxicity is 30% with an equivalence interval between 25-33% of pts. With an anticipated 3 dose levels ( DL) and an option for a DL-1, up to 18 pts may be required to determine the MTD and RP2D. Phase II: Any pt treated at the RP2D within phase Ib will be rolled into the phase II analysis for efficacy. With a planned 24 evaluable pts in phase II, the target ORR will be 60%, which was selected due to a recent phase I/II study of pirtobrutinib enrolling a similar CLL pt population demonstrating an ORR of the drug ~63%. ORR will be summarized by the observed proportion and an exact one-sided 95% confidence interval (Clopper-Pearson method). With 24 evaluable pts, the lower bound of the confidence interval will be approximately 17-20% below the observed proportion for observed ORR near 60%, which is an acceptable level of precision in a dose expansion cohort.

Portable SERS-based lateral flow immunoassay strips with self-calibration for detection of a prostate cancer biomarker

Serum prostate-specific antigen (PSA) is thought to be the most vital indicator for early identification, staging and monitoring of prostate cancer (PCa). Although lateral flow immunoassay (LFA) has demonstrated limitless promise for point-of-care testing (POCT) and has drawn increasing interest and attention, there are significant restrictions on the assay's sensitivity and quantitative capability. Surface-enhanced Raman spectroscopy-based LFA (SERS-LFA) technique integrates the great sensitivity of SERS with the simplicity, rapidity, and usability of the LFA technique, making it ideal for POCT. In this paper, we propose a sensitive self-calibrating SERS-LFA platform, which uses Au@MBN@Ag@PSA NPs as a SERS immunoprobe for the specific recognition of PSA and loads graphene oxide/gold nanoparticles (GO/Au NPs) on nitrocellulose (NC) membranes as an internal standard (IS) molecule. The SERS-LFA platform's detection accuracy is increased through dynamic calibration of the characteristic signals, which is accomplished by detecting the immunoprobe and IS signals simultaneously and computing their respective signal intensity ratios. The self-calibrated SERS-LFA platform demonstrated a 1.65-fold improvement in reproducibility over the conventional SERS-LFA, and PSA could only be detected to a limit of 0.08 ng/mL, meaning that it was 3.5-fold lower than the conventional SERS-LFA platform. The spike recovery experiments yielded recoveries of 96.16∼104.53% with RSD values of 9.37%, 8.66%, and 3.49%, respectively, demonstrating that our self-calibrated SERS-LFA platform for PSA quantification has an acceptable level of precision and has great prospect for early screening of PCa and other diseases.

Soybean (Glycine max) Cropland Suitability Analysis in Subtropical Desert Climate through GIS-Based Multicriteria Analysis and Sentinel-2 Multispectral Imaging

Soybean (Glycine max) is a protein-rich oilseed crop that is extensively used for cooking oil and poultry feed and faces significant challenges due to adverse global climatic conditions aggravated by the ongoing climate crisis. In response to this critical issue, this study was initiated to assess suitable zones for soybean cultivation, aiming to facilitate informed land use decisions within the semi-arid terrestrial ecosystem. Through the utilization of geostatistical interpolation, data layers encompassing soil, irrigation water, land use and land cover, topographic features, and climate information were generated and overlaid based on criterion weightage derived from the Analytic Hierarchy Process. The accuracy of land use and land cover was rigorously evaluated, yielding a 70% overall accuracy and a Kappa (K) value of 0.61, signifying an acceptable level of precision. Validation through the Receiver Operating Characteristic curve for soybean crop suitability demonstrated a highly satisfactory area under the curve of 0.738. The study estimates that out of 172,618.66 hectares, approximately 47.46% of the land is highly suitable (S1) for soybean production, followed by 21.36% moderately suitable (S2), 11.91% marginally suitable (S3), 7.00% currently not suitable (N1), and 12.28% permanently not suitable (N2). Conclusively, the findings suggest that the study area exhibits conducive climatic conditions, optimal soil health, and access to quality irrigation water, all of which have the potential to support soybean crops with improved agronomic practices. This investigation offers valuable insights to both farmers and policymakers concerning irrigation water quality, agricultural productivity, and soil degradation.

Systematic Process for Determining Field-Sampling Effort Required to Know Vegetation Changes in Large, Disturbed Rangelands Where Management Treatments Have Been Applied

Adequate numbers of replicated, dispersed, and random samples are the basis for reliable sampling inference on resources of concern, particularly vegetation cover across large and heterogenous areas such as rangelands. Tools are needed to predict and assess data precision, specifically the sampling effort required to attain acceptable levels of precision, before and after sampling. We describe and evaluate a flexible and scalable process for assessing the sampling effort requirement for a common monitoring context (responses of rangeland vegetation cover to post-fire restoration treatments), using a custom R script called “SampleRange.” In SampleRange, vegetation cover is estimated from available digital-gridded or field data (e.g., using the satellite-derived cover from the Rangeland Assessment Platform). Next, the sampling effort required to estimate cover with 20% relative standard error (RSE) or to saturate sampling effort is determined using simulations across the environmental gradients in areas of interest to estimate the number of needed plots (“SampleRange quota”). Finally, the SampleRange quota are randomly identified for actual sampling. A 2022 full-cycle trial of SampleRange using the best available digital and prior field data for areas treated after a 2017 wildfire in sagebrush-steppe rangelands revealed that differences in the predicted compared with realized RSEs are inevitable. Future efforts to account for uncertainty in remotely sensed−based vegetative products will enhance tool utility.

B-222 Validation of a qPCR Method for Qualitative Detection of Monkeypox Virus

Abstract Background The 2022 Monkeypox virus (MPXV) outbreak became a global concern, prompting a multidisciplinary response to increase surveillance and isolate suspected and confirmed cases to reduce disease spread. Quantitative PCR (qPCR) is capable of detecting small amounts of DNA or RNA, and can be used to quickly and accurately confirm MPXV cases, even at early stages of infection, which is crucial for outbreak control and management. Methods qPCR was performed on a 384-well plate with a total reaction volume of 20 μl consisting of 9 μL Acrometrix Monkeypox DNA Positive Control at serial dilutions, 10 μL BactoPure Master Mix, and 1 μL TaqMan Monkeypox Virus Microbe Detection Assay. Positive control dilutions 103, 102, 101, and 100 were diluted with TE Buffer. qPCR was performed on two different Quantstudio 12K Flex instruments. Results The qPCR method validation was performed by calculating precision, accuracy, and linearity on serial dilutions of Acrometrix Monkeypox Virus DNA Positive Control. Precision testing was performed on 2 levels of control: low (101) and high (103) over 5 days with 4 repeats per day. Accuracy and linearity testing were performed on 4 levels with 3 repeats. Coefficient of variation (CV) was less than 5%, specifically 0.9% for the low control and 4.3% for the high control, indicating an acceptable level of precision. Percent recovery fell close to 100%, specifically within 101%-103% for all controls, indicating the results fell close to the expected value. Linearity R2 was close to 1, specifically 0.984, demonstrating the results are proportional to the concentration analyzed. Conclusion Validation of MPXV detection through qPCR was successful. Development and validation of qPCR assays for the detection of positive MPXV cases is essential for managing future outbreaks and combatting future pathogenic strains.

Determination of process contaminants 2- and 3-MCPD esters and glycidyl esters in palm-based glycerol by indirect analysis using GC-MS

Esters of 2- and 3-monochloropropanediol (2-MCPDE, 3-MCPDE) and glycidol (GE) are regarded as process contaminants that are found in refined vegetable oils and oil-based foods. Since glycerol is produced during fat splitting, saponification and biodiesel production, it is important to have methods for determining contaminants that might be formed during these processes. Due to the use of glycerol as a food additive, data on the presence of compounds of toxicological concern, including 3-MCPD, are of interest. This study focuses on modifying the indirect analysis of 2-MCPDE, 3-MCPDE and GE using GC-MS based on the AOCS Official Method Cd 29a-13, validating the modified method, and quantifying 2-MCPDE, 3-MCPDE and GE in glycerol. The AOCS Cd 29a-13 method was modified at the initial stage of sample preparation in which the targeted esters were extracted from glycerol by vortex-assisted extraction before sample analysis. This modification was performed based on the polarity of all compounds involved. The calibration functions for all analytes were fitted to linear regression with R 2 above 0.99. Limits of detection (LOD) 0.02, 0.01 and 0.02 mg kg−1 were obtained for 2-MCPDE, 3-MCPDE and GE, respectively. Spiked glycerol with 3-MCPDE and 2-MCPDE (0.25, 0.51 and 1.01 mg kg−1) and GE (0.58, 1.16 and 2.32 mg kg−1) were used for recovery and precision measurements. Recoveries of 100-108%, 101-103%, and 93-99% were obtained for 2-MCPDE, 3-MCPDE and GE, respectively. Acceptable precision levels with relative standard deviations ranged from 3.3% to 8.3% were obtained for repeatability and intermediate precision. The validated method was successfully applied for the analysis of the target compounds in refined glycerol from commercial plants, which showed that 2-MCPDE, 3-MCPDE and GE levels in the analysed samples were below the detection limit.

Thermo-hygro-mechanical coupling model based on discrete element method to simulate hygrothermal-induced damage of PA6/GF30 material

The present contribution deals with a thermo-hygro-mechanical coupling model based on Discrete Element Method to numerically simulate hygrothermal transfers and their influence on the mechanical behaviour and interfacial damage of composite materials. For application purposes, we consider the context of a 30% glass fibre reinforced polyamide 6 material which is notably used in automotive industry due to its advantageous strength-to-weight ratio. Firstly, a coupled hygrothermal model based on boundary layer theory and the analogy between Fickian mass transfer and heat transfer by conduction is proposed. This is validated in terms of water concentration and water concentration gradient fields, by comparison with Finite Element Method calculations through the simulation of water absorption process in a PA6 material sample. Secondly, a swelling model is proposed to couple hygrothermal transfers to the mechanical behaviour of a material modelled using the hybrid lattice–particle approach. Finally, the hydric swelling-induced interfacial debonding of glass fibre reinforced polyamide 6 material is simulated. Results exhibit the pertinence of the proposed Discrete Element Method based thermo-hygro-mechanical model to reproduce such a process and yields stress and displacement fields with an acceptable level of precision.

Reliability of Universal-Platform-Based Voice Screen Application in AVQI Measurements Captured with Different Smartphones.

The aim of the study was to develop a universal-platform-based (UPB) application suitable for different smartphones for estimation of the Acoustic Voice Quality Index (AVQI) and evaluate its reliability in AVQI measurements and normal and pathological voice differentiation. Our study group consisted of 135 adult individuals, including 49 with normal voices and 86 patients with pathological voices. The developed UPB "Voice Screen" application installed on five iOS and Android smartphones was used for AVQI estimation. The AVQI measures calculated from voice recordings obtained from a reference studio microphone were compared with AVQI results obtained using smartphones. The diagnostic accuracy of differentiating normal and pathological voices was evaluated by applying receiver-operating characteristics. One-way ANOVA analysis did not detect statistically significant differences between mean AVQI scores revealed using a studio microphone and different smartphones (F = 0.759; p = 0.58). Almost perfect direct linear correlations (r = 0.991-0.987) were observed between the AVQI results obtained with a studio microphone and different smartphones. An acceptable level of precision of the AVQI in discriminating between normal and pathological voices was yielded, with areas under the curve (AUC) displaying 0.834-0.862. There were no statistically significant differences between the AUCs (p > 0.05) obtained from studio and smartphones' microphones. The significant difference revealed between the AUCs was only 0.028. The UPB "Voice Screen" application represented an accurate and robust tool for voice quality measurements and normal vs. pathological voice screening purposes, demonstrating the potential to be used by patients and clinicians for voice assessment, employing both iOS and Android smartphones.

“One Metric to Rule Them All”: A Common Metric for Symptoms of Depression and Generalized Anxiety in Adolescent Samples

There is a significant degree of heterogeneity in scales that purport to measure depression and generalized anxiety in adolescent samples, which makes it difficult to directly compare scores across studies. The aim of the current study is to develop a common metric that facilitates the comparison of scores from different but related scales of depression and generalized anxiety using a large adolescent sample. A nonequivalent-anchor-test design in conjunction with simultaneous calibration was used to equate and develop a common metric for six different scales. The common metric provided scores with acceptable levels of precision across the −1 to 3 range on θ, which represents the more severe and often clinical end of the spectrum. Thus, in the current study, we identified a coherent common metric that is closely aligned with the “distress” subfactor of the Hierarchical Taxonomy of Psychopathology model. Additional validation testing in independent samples is now required.

A Review on Process Modeling and Simulation of Cryogenic Carbon Capture for Post-Combustion Treatment

The cryogenic carbon capture (CCC) process is a promising post-combustion CO2 removal method. This method is very novel compared with conventional and well-developed methods. However, cryogenic carbon capture is not yet commercially available despite its techno-economic benefits. Thus, a model-based design approach for this process can provide valuable information. This paper will first introduce the cryogenic carbon capture process. Then, a comprehensive literature overview that focuses on different methods for modeling the process at the component level will be given. The modelling methods which are deemed most effective are presented more in depth for each of the key system components. These methods are compared with each other in terms of complexity and accuracy and the simplest methods with an acceptable level of precision for modelling a specific component in the CCC process are recommended. Furthermore, potential research areas in modeling and simulation of the CCC process are also highlighted.

Sample size determination: A practical guide for health researchers.

Although sample size calculations play an essential role in health research, published research often fails to report sample size selection. This study aims to explain the importance of sample size calculation and to provide considerations for determining sample size in a simplified manner. Approaches to sample size calculation according to study design are presented with examples in health research. For sample size estimation, researchers need to (1) provide information regarding the statistical analysis to be applied, (2) determine acceptable precision levels, (3) decide on study power, (4) specify the confidence level, and (5) determine the magnitude of practical significance differences (effect size). Most importantly, research team members need to engage in an open and realistic dialog on the appropriateness of the calculated sample size for the research question(s), available data records, research timeline, and cost. This study aims to further inform researchers and health practitioners interested in quantitative research, so as to improve their knowledge of sample size calculation.

A Design-assisted Spectrofluorometric Method Utilizing a One-pot Fluorescent Probe for the Quantitation of some Calcium Channel Blockers

Based on their reaction with highly fluorescent carbon quantum dots (CQDts), a precise and reliable spectrofluorometric approach was developed for the determination of three calcium channel blockers. The studied drugs are: lercanidipine, nimodipine and nifedipine. (CQDts) were produced using a one-step hydrothermal method with ascorbic acid as the carbon source. The produced CQDts were capped by alcohol to create yellow emitters displaying a high fluorescence emission at 524 nm when excited at 325 nm. The fluorescence intensity of CQDts was noticeably quenched by each of the three calcium channel blockers. The relation between their concentrations and fluorescence quenching is linear over the concentration range of 0.5–20 µg/mL for each of the three drugs. A full factorial design was used to optimize the effect of variable factors. Therefore, under optimum experimental design conditions, the detection limits for lercanidipine, nimodipine, and nifedipine were 0.11 ± 1.09, 0.10 ± 0.25 and 0.12 ± 0.71 µg/mL, respectively. The LOQ was 0.33, 0.30, and 0.37 µg/mL respectively. The quenching of fluorescent CQDts occurred through the inner filter effect (IFE) for nimodipine, while it was mixed with dynamic quenching for lercanidipine and nifedipine. The proposed method was effectively used to determine the cited drugs in their pharmaceutical products and had an acceptable level of precision. The selectivity of the CQDts system towards the studied drugs was examined indicating no interference from interfering species.

LoRaWAN: Lost for Localization?

Nowadays, the flexible localization solution for various devices for workplace safety is one of the most demanding research questions. Notably, it is expected to provide an acceptable level of precision in different types of environments empowered by wearable technology and Internet-of-Things (IoT) devices. Existing leading localization technologies are adapted for certain conditions, for example, Wi-Fi, Bluetooth low energy (BLE), and ultra-wideband (UWB) are used for indoor areas and various global navigation satellite system (GNSS)-based ones for outdoors. This work focuses on investigating the long-range wide-area network (LoRaWAN) (868-MHz band) as a potential candidate to bridge this gap, being one of the most reliable and recognized communication technologies for the Industrial IoT (IIoT). In the past, the research community had a lot of critics with respect to the applicability of LoRaWAN for localization, while the vision is facing tremendous change over the past two years. The purpose of this work is to assess the feasibility of LoRaWAN as a localization solution for work safety applications in the industrial scenario from different angles. The work is based on two measurement campaigns conducted at the Brno University of Technology (BUT), Brno, Czech Republic, and the University Politechnica of Bucharest (UPB), Bucharest, Romania. The campaigns cover both indoor and outdoor scenarios and provide the practical limitations of the positioning in standalone and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${k}$ </tex-math></inline-formula> -nearest neighbors ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${k}$ </tex-math></inline-formula> -NN) powered localization systems. According to the results, LoRaWAN-based localization with relatively dense gateways (GWs) deployment allows for achieving a meter-level accuracy, which may be suitable for the localization of workers.

Abstract 52: Analytical validation of the Resolution HRD plasma assay used to identify mCRPC patients with mutations, including homozygous deletions, in DNA repair genes as a companion diagnostic for niraparib

Abstract Tumor cells of metastatic castration-resistant prostate cancer (mCRPC) patients with homologous recombination deficiency (HRD) are highly sensitive to the blockade of DNA single-strand break repair via the inhibition of the poly(adenosine diphosphate-ribose) polymerase (PARP) family of nuclear proteins. Niraparib is a highly selective PARP inhibitor, with activity against PARP-1/2 DNA-repair polymerases, and the Resolution HRD assay is being developed as a companion diagnostic for niraparib. Detection of HRD in cell free DNA (cfDNA) isolated from blood is minimally invasive and is of special benefit to mCRPC patients, many without accessible lesions. The Resolution HRD assay identifies patients with substitutions, insertions, deletions, and homozygous deletions of the ATM, BRCA1, BRCA2, BRIP1, CDK12 (except homozygous deletions), CHEK2, FANCA, HDAC2, and PALB2 genes by targeted NGS sequencing of cfDNA isolated from plasma. Analytical performance of the Resolution HRD assay was validated using cfDNA from mCRPC patient plasma, cfDNA from healthy donor plasma, and contrived samples with a wide spectrum of technically challenging genetic aberrations along with CRISPR-engineered human cell lines with ATM and BRCA2 gene deletions. The LOD95 was established for substitutions, insertions, deletions, and homozygous deletions for genes represented in the HRD panel with variant types including complex indels, long indels, and challenging genomic settings including homopolymeric and GC-rich regions. mCRPC specimens were used to confirm an acceptable level of precision near 1X LOD and 2-3X LOD concentrations for all 4 variant types. No false-positives were detected in any samples from healthy donors. Resolution HRD has been validated to give consistent results across the 15-30 ng input range. Studies to confirm accuracy of the Resolution HRD test results using a validated orthogonal method will be presented. The Resolution HRD assay offers highly sensitive, specific, and robust test results, and meets analytical requirements for clinical applications. It is intended as a companion diagnostic to niraparib in combination with abiraterone acetate plus prednisone (AAP) for the treatment of mCRPC patients. Citation Format: Julia Pollak, Kristy Potts, PuiYee Chan, Chen-Hsun Tsai, Angela Liao, Carly Garrison, Taylor Brown, Paul Stull, Zhen Li, Christine Baker, Kavita Garg, Ira Pekker, Michael Farabaugh, Michael Gormley, Lesley Farrington, Katherine Bell, Usha Singh. Analytical validation of the Resolution HRD plasma assay used to identify mCRPC patients with mutations, including homozygous deletions, in DNA repair genes as a companion diagnostic for niraparib [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 52.

Numerical analysis of heating aerosol carbon nanofluid flow in a power plant recupesrator with considering ash fouling: a deep learning approach

The main goal of this research is to optimize a corrugated high-temperature helical recuperator filled with aerosol-carbon-black nanofluid. This heat exchanger has inner semi-sphere-shaped corrugations with different diameters. In this study, the related effects of different geometric parameters according to the heat-hydraulic performance of the studied helical heat exchanger are analyzed. Moreover, to select the optimal model, the hydraulics-thermal index is examined and its maximum value is introduced as the optimal model. The Discrete Phase, Model (DPM) approach is also used to model multi-phase currents. In order to numerically simulate and solving the governing equations, the Ansys Fluent software, SIMPLE algorithm and the finite volume method were used. As it is realized, the helical corrugated recuperator with corrugation diameter of d=10mm and filled with nanofluid (NF) with volume concentration of φ=0.7% has the maximum thermal-hydraulic performance evaluation criteria. Then, a deep learning method is applied to data in order to obtain the average Nusselt number (Nuav), the pressure drop (ΔP) between outlet and inlet, the friction factor (f), and the PEC for all values of the volume fraction, mass flow rate, and turbulators diameter within the examined range. To this end, an Artificial Neural Network (ANN) with one hidden-layer is employed. The results indicate that the ANN can model the investigated phenomenon with acceptable level of precision.