Conventional Sampling Techniques Research Articles

First Report on Clinical Feasibility of Dried Blood Spot Technique for Hemoglobin Estimation in Cholistani Cattle

Background: The dried blood spot (DBS) technique using filter papers has revolutionized the conventional blood sampling techniques through ease of blood collection, storage and transport. Various analytes (such as hormones, antigens, antibodies and hematochemical attributes) are being estimated through DBS globally. However, this technique has not yet been implied in Pakistan. This research work is the first of its kind regarding hemoglobin (Hb) estimation in Cholistani cattle (n=63) blood through DBS technique using filter paper.Methods: Three methods of Hb estimation were implied in the present study viz. through veterinary hematology analyzer (HbA), and two indirect cyanmethemoglobin methods (HbIC and HbICX) using measured (20µL) and unmeasured blood drops on the filter paper, respectively.Results: Results revealed that HbA and HbIC were non-significantly (P≥0.05) different from each other, being different from HbICX (P≤0.05). The HbICX gave overestimated values of Hb as compared to HbA and HbIC. The sensitivity, specificity, positive predictive value, and negative predictive value for HbIC were higher being 86.1%, 88.3%, 88.0%, and 86.0%, respectively as compared to the lower values of 45.0%, 12.0%, 12.0% and 45.0%, for HbICX. Bland and Altman test revealed a better level of agreement between HbA and HbIC. Around the mean difference line, there was no proportional bias in data distribution (Mean= -0.16, 95% CI= 0.34 to -0.67). Similarly, measures attained through Cronbach alpha and intraclass correlation coefficient between HbA and HbIC were higher being 0.703 and 0.825 values for single and average, respectively, as compared to the values of 0.200 and 0.333 between HbA and HbICX.Conclusion: It is concluded that the indirect cyanmethemoglobin method for Hb estimation is reliable and accurate for cattle blood, if a measured quantity of blood drop is taken on a filter paper. We recommend this DBS technique for Hb estimation in cattle blood for resource-poor settings and for livestock herds being reared distantly from the laboratories. For future, it is recommended that DBS technique with various other modifications and for other hematochemical biomarkers may be validated for livestock blood.Keywords: Dried blood spot; Hemoglobin; Cholistani cattle

The Role of Islamic Financial Education in Encouraging Customer Investment Behavior in Islamic Banking in Yogyakarta, Indonesia

This paper investigated the moderating effect of Islamic financial education on the relationship between information management and customer perception regarding the increase in investments at Bank Syariah Indonesia, using conventional sampling techniques for data collection from respondents in Yogyakarta. A closed questionnaire comprising 35 items was prepared and tested before the commencement of the study. Path analysis in PLS was utilized as the primary tool to analyze the 141 respondents who completed the survey. The research revealed that the moderating factors have both direct and indirect moderation effects on customer financial investments in Bank Syariah Indonesia, indicating that information management and customer perception are crucial factors in enhancing customer investments. Accordingly, the study was limited to the collection of quantitative data using a semi-structured questionnaire from Yogyakarta, and there is an opportunity to test these findings in other major cities, including those in other developing countries. From a practical perspective, this study elucidates that Islamic financial education plays a significant role in increasing the value of customer investments in Bank Syariah Indonesia, thereby potentially expanding the market share of Islamic banks in Indonesia.

Microsampling and conventional sampling techniques for quantification of tacrolimus in blood samples: A systematic review

Microsampling and conventional sampling techniques for quantification of tacrolimus in blood samples: A systematic review

Metabarcoding advances agricultural invertebrate biomonitoring by enhancing resolution, increasing throughput and facilitating network inference

Abstract Biomonitoring of agriculturally important insects is increasingly vital given our need to understand: (a) the severity of impacts by pests and pathogens on crop yield and health and (b) the impact of environmental change and land management on insects, in line with sustainable development and global conservation targets. Traditional entomological traps remain an important part of the biomonitoring toolbox, but sample processing is laborious and introduces latency, and accuracy can be variable. The integration of molecular techniques such as environmental DNA and DNA metabarcoding into insect biomonitoring has gained increasing attention, but the advantages of doing so, the kind of data this can generate, and how easily and effectively molecular analyses can be integrated with the diverse types of entomological traps currently used remains relatively unclear. In this review, we examine how combining DNA metabarcoding with a range of conventional and unconventional entomological sampling techniques can advance biomonitoring in a way that is useful to researchers and practitioners. We highlight some of the key challenges and how to mitigate them, using examples of its integration with different sampling methods from the literature (e.g., interception, pitfall and sticky traps) to demonstrate efficacy and suitability. We discuss how metabarcoding data can be used to infer ecological networks, emphasizing the importance of this as a framework for understanding species interactions and ecosystem functioning for more effective and descriptive biomonitoring. Finally, future advances in biomonitoring are highlighted, alongside recommendations of best practice for researchers both new to and experienced in invertebrate biomonitoring with metabarcoding.

A Study of Select Variables Impacting Buying Behaviour of Electric Cars In India

The automobile industry is currently undergoing a significant transformation in its approach to transportation, primarily driven by increased awareness of climate change and limited resources. The recent resurgence of electric vehicles in the market can be attributed to various factors, including advancements in battery technology and government policies aimed at reducing vehicle emissions. This research focused on examining the factors that influence consumer purchasing behavior regarding electric cars in India. Primary data was collected through a self-administered questionnaire distributed to consumers. The survey sample was selected using a combination of conventional and snowball sampling techniques, drawing participants from the target population. The study and survey took place in the Delhi/NCR region from January to February 2023. A total of 649 questionnaires were distributed, out of which 324 were returned. After analysing the data, 214 fully completed responses were used for further analysis. The findings indicated that financial barriers, concerns about vehicle performance, lack of charging infrastructure, environmental awareness, societal influence, and knowledge of electric vehicles all significantly impact the decision-making process when considering the purchase of electric vehicles.

Can capillary microsampling facilitate a clinical pharmacokinetics study of cefazolin in critically ill children?

Aim: Pharmacokinetic studies in children are limited, in part due to challenges in blood sampling. We compare the use of capillary microsampling and conventional sampling techniques in pediatric patients to show results that can be used in the pharmacokinetic analysis of Cefazolin.Patients & Methods: Paired blood samples (n=48) were collected from 12 patients (median age/weight 49months/18kg).Results: The United States Federal Drug Administration incurred sample reanalysis acceptance criteria was used and identified 79% of paired samples achieved a difference of less than 20% in magnitude with a capillary microsampling bias of -10% (SD 20%). With exclusion of PK outliers, this rose to 88%.Conclusion: Capillary microsampling is reliable, meets acceptance criteria and can be used in pharmacokinetic studies.ACTRN: 12618001469202.

Generating Manufacturing Distributions for Sampling-based Tolerance Analysis using Deep Learning Models

Sampling-based tolerance analysis is a powerful tool for evaluating the quality of functional products, but requires realistic manufacturing distributions. However, the determination of resulting manufacturing distributions is usually associated with a high financial and time expenditure, especially for novel technologies such as Additive Manufacturing. Usually, sampling techniques are used to reproduce the original distribution of manufacturing variations based on statistical moments. In most cases, simplifying assumptions are made for this purpose, potentially leading to an inadequate representation of the correlation between machine and process parameters in the resulting distribution. In the worst case, this can lead to a falsification of the tolerance analysis results. Aiming to address this challenge, this paper presents an approach to imitate real-world manufacturing distributions using generative Machine Learning techniques based on Deep Learning with small real data sets. This enables a realistic reproduction of quasi-real manufacturing distributions and omits conventional sampling techniques. The general procedure and its applicability are shown via illustrative use cases from the tolerancing domain.

Mercury distribution, mobilization and bioavailability in polluted sediments of Scheldt Estuary and Belgian Coastal Zone

In this study, the vertical distribution of mercury (Hg) in estuarine and marine sediment porewaters and solid phases was assessed by conventional and passive sampling techniques in the historically polluted Scheldt Estuary and Belgian Coastal Zone (BCZ). The Diffusive Gradients in Thin-films (DGT) measured labile Hg concentrations (HgLA) were mostly lower than the porewater Hg concentrations (HgPW), and they also presented different vertical distribution patterns. Still high Hg concentrations in the sediment solid phases, comparable to the historical ones, were observed. Even though pH, redox potential and dissolved sulfide concentration could influence the Hg biogeochemical behaviour, organic matter (OM) played a key role in governing Hg mobilization from sediment solid phase to porewater and in its partitioning between porewater and solid phase over depth. In the marine sediments, where OM had a marine signature, higher labile Hg concentrations in the porewater and faster resupply from the solid phase were observed. The DGT technique showed significant potential not only for the measurement of bioavailable Hg fractions in porewater, but also for the assessment of kinetic parameters governing the release of labile Hg species from the solid phase with the assistance of the DGT Induced Fluxes in Sediments (DIFS) model.

Diagnostic accuracy and interobserver agreement of cholangioscopy for indeterminate biliary strictures: A single-center experience

Background and study aimsCharacterization of indeterminate biliary strictures (IDBS) still represents a major challenge. Digital single-operator cholangioscopy (DSOC) could potentially overcome limits of conventional biopsy and brush sampling. The aim of this study was to compare diagnostic accuracy of visual evaluation and DSOC-guided biopsies to conventional trans-papillary sampling techniques and to evaluate the inter-observer agreement (IOA) on visual diagnosis. Patients and methodsAll consecutive patients undergoing DSOC-guided biopsy after conventional sampling techniques for IDBS during a six—year period were retrospectively evaluated. Final diagnosis was based on histological evaluation of the surgical specimen if available or a clinical follow-up of at least 6 months. For IOA, 20-second DSOC clips were retrospectively reviewed by 6 experts and 6 trainees and classified according to the Monaco Classification. ResultsThirty-five patients underwent DSOC for IDBS in the study period; 14 patients (F = 9) with a median age of 64 years (range 53–76) met the study aim. After DSOC, strictures location was changed in three patients (additional yield of 21.4 %). Intraductal DSOC-guided biopsy were technically successful in all cases, with an adequacy of 92.8 %. No adverse events were recorded. Final diagnosis was benign disease in five cases and cholangiocarcinoma in the others. For IOA, 29 videos were evaluated with almost perfect agreement for final diagnosis (kappa 0.871; agreement 93.1, p <0.001), although overall accuracy of DSOC visual finding was 73.6 % and 64.4 % for experts and trainees, respectively. ConclusionsDSOC could improve diagnostic accuracy for IDBS, since it showed high sensitivity for visual finding and high specificity for DSOC guided-biopsy. Visual diagnosis seems reliable for diagnosis using the Monaco Classification.

Study of γ-Ray Spectrum Measurement Analysis Algorithm of Radioactive Solid Waste Steel Boxes

Abstract In accordance with safety requirements for the near-surface disposal of low and medium-level radioactive solid waste, accurate identification and measurement of radionuclide types and activities within steel boxes containing such waste are necessary. Conventional sampling techniques are impractical due to nonuniform internal filling and radioactive distribution in the steel boxes used for storage. Nondestructive measurement analysis techniques offer significant advantages by providing comprehensive measurements without causing damage to the steel boxes or generating secondary waste. Therefore, nondestructive techniques are widely applicable and superior to chemical analysis methods. This study presents an algorithm for analyzing γ-ray spectrum measurements of radioactive solid waste steel boxes by combining the traditional computed tomography (CT) principle with a discrete treatment approach. The progressive split voxel measurement method is utilized to discretely handle the radioactive solid waste steel boxes during the measurement and calculation process while considering the impact of voxel interactions on detection efficiency. A detection efficiency calibration model is established using Monte Carlo (MC) simulation in conjunction with the algebraic reconstruction technique (ART). Additionally, an inversion correction of the efficiency for the physically coincident portion of the detected voxel volume is performed during the measurement process. The proposed algorithm is initially applied to the analysis platform of steel boxes that store FA-IV-type radioactive solid waste. The algorithm's performance is further investigated and validated using standard radioactive sources with known activity levels. The results indicate that the relative deviation between the reconstruction results and the nominal values of radioactive activities in the steel boxes is less than 30%. These findings align with the expected results and satisfy the measurement analysis and warehousing processing requirements for waste generated from the decommissioning of China's 101 nuclear reactor. The proposed algorithm holds great potential for widespread application in related detection work.

Comparative investigations on microextraction and conventional air sampling techniques: challenges and future directions

Comparative investigations on microextraction and conventional air sampling techniques: challenges and future directions

Comparative investigations on microextraction and conventional air sampling techniques: challenges and future directions

Comparative investigations on microextraction and conventional air sampling techniques: challenges and future directions

Optimization of bioanalysis of dried blood samples

IntroductionPharmacokinetic/pharmacodynamic modelling has emerged as a valuable technique for understanding drug exposure and response relationships in drug development. Pharmacokinetic data are often obtained by taking multiple blood samples, which may disturb physiological parameters and complicate study designs. Wearable automatic blood sampling systems can improve this limitation by collecting dried blood samples at programmable time points without disrupting cardiovascular parameters. It is the objective of this study to evaluate the bioanalysis of DBS in comparison to conventional blood sampling techniques and to optimize the recovery of various compounds spiked into canine blood dried on filter paper tape. MethodsIncubated blood samples from Beagle dogs were spiked with 16 different compounds and half of the whole blood sample was centrifuged to obtain plasma. After the dried blood sample drops were dried, liquid chromatography-mass spectrometry methods were used to analyze the samples. The study explored different anticoagulants, sample preparation methods and technical approaches to best determine the compound concentrations in dried blood samples. ResultsWith the two anticoagulants tested and using the optimized sample preparation methods and technical approaches we employed, the bioanalysis of dried blood samples can provide equivalent results to conventional blood sampling techniques. DiscussionAutomated blood sampling systems have the potential to provide increased numbers of blood samples, providing substantially more Pharmacokinetic data within safety pharmacology studies without disrupting physiological parameters. They can provide a viable alternative to traditional methods of obtaining blood for various other types of studies or analyses.

Comparison of Microsampling and Conventional Sampling Techniques for Quantification of Warfarin in Blood Samples: A Systematic Review

Warfarin is a vitamin K antagonist (VKAs) anticoagulant associated with interindividual patients’ response to therapy, narrow therapeutic index, and serious adverse drug events. Monitoring ensures efficacy and safety by measuring drug concentration in the bloodstream, which demands blood or plasma samples from patients through conventional sampling. Conventional sampling often requires invasive methods that may be uncomfortable for patients. Microsampling offers an opportunity to reduce the burden of multiple blood sampling on patients and simplifies the process of sample transportation and storage. This systematic review describes conventional and microsampling techniques for quantifying warfarin in human blood samples and the bioanalytical method employed to perform the analysis. Related studies (537) were screened from several databases and narrowed down into 12 eligible articles, which were then used to fulfill the purpose of this review in a narrative form. It is concluded that while there are still limited studies regarding the application of microsampling for warfarin quantification in patients, there has been evidence of comparable plasma and micro samples results, highlighting the potential for future development of routine monitoring using the microsampling technique.

Quantitative analysis of trace elements in technological materials using online-laser ablation of solids in liquids (online-LASIL)

To overcome the challenges of the 21st century, the demand for novel materials which outperforms the limits of previous material classes is high. However, the elemental composition determines crucial material properties from the bulk stoichiometry down to ultra-trace impurities. Therefore, a precise analytical characterization is inevitable to establish a connection between composition and function.For this purpose, conventional solid sampling techniques could be applied. However, matrix-matched standards are indispensable for quantitative analysis and are often unavailable in the case of technological materials. To overcome this limitation online-Laser Ablation of Solids in Liquids (online-LASIL) has been proposed recently, which combines the advantages of solution-based analysis and solid sampling techniques. However, this technique has only been applied to determine sample stoichiometry.In this work, major improvements of the online-LASIL approach were reported by the controllable segmentation of the carrier solution, leading to an improved washout behavior of the ablated material, enabling the quantitative investigation at trace levels. The accuracy of this improved measurement setup is validated by the quantitative analysis of trace elements in the standard reference material (SRM) NIST612. To demonstrate the applicability of this method, silicon carbide (SiC), a wide bandgap semiconductor, was analyzed. With the improved online-LASIL method, an Al-doped region, which is only constant for the first 250 nm, was successfully quantified.

Prevalence and risk factors associated with canine dermatophytoses among dogs in Kwara and Osun States, Nigeria

Background: Dermatophytosis (ringworm) is a zoonotic fungal skin infection caused predominantly by Microsporum canis, Microsporum gypseum and Trichophyton spp. It is highly transmissible and, while normally self-limiting, could be problematic due to its potential to cause disease in certain human populations. The occurrence and associated risk factors of dermatophytoses in dogs presented at three veterinary clinics in Osogbo, and Ilorin, Nigeria between July and November 2019 were investigated in this study.&#x0D; Methodology: This was a descriptive cross-sectional study of 325 dogs with lesions suggestive of dermatophytosis, selected by simple random sampling from three veterinary clinics in Osogbo and Ilorin, purposively selected for the study due to high patronage of the veterinary hospitals by dog owners. Using conventional mycological sampling techniques, plucked hairs and skin scrapings were obtained the dogs. The samples were emulsified in 10% potassium hydroxide, examined microscopically for fungal elements and cultured using standard mycological procedures. Information on dog demographic characteristics and risk factors for dermatophytosis were collected using structured questionnaire. The association between risk factors and demographic variables with the occurrence of dermatophytoses was determined using Chi-square test (with Odds ratio and 95% confidence interval) and p value &lt; 0.05 was considered statistically significant.&#x0D; Results: Positive cultures for dermatophytes were obtained from samples of 48 (14.8%) dogs with M. canis 37.5% (18/48), M. gypseum 27.0% (13/48) and T. mentagrophytes 8.3% (4/48). Other fungi identified were Aspergillus flavus 12.5% (6/48) and Malassezia canis 12.5% (6/48). The age distribution of positive dogs were &lt; 1 year (50.0%, n=24), 1-3 years (29.2%, n=14) and &gt; 3 years (20.8%, n=10), while the risk factors associated with dermatophytosis included sex of dogs (p=0.0428), history of dermatophytosis (p&lt;0.0001), clinical presentation (p&lt;0.0001) and lesion type, especially kerion and pustular lesions (p=0.0297).&#x0D; Conclusion: These findings established the occurrence of dermatophytosis in dogs kept for companionship (i. e., pets), security and breeding purposes in the two States in Nigeria. Our findings underscore the need for routine mycological investigations in dogs to facilitate early detection of cases and prompt institution of treatment interventions, thereby preventing zoonotic transmission of dermatophytes to their owners, handlers and veterinarians.

Abundance of fin whales in West Greenland in 2007

An aerial line transect survey of fin whales (Balaenoptera physalus) conducted off West Greenland in 2007 was used to estimate the current abundance of fin whales on the summer feeding ground. A total of 24 sightings of fin whale groups were collected during 8,632km of survey effort in sea states &lt;5. Based on conventional distance sampling techniques an abundance of 4,359 whales (95% CI 1,879–10,114) was estimated. The survey was conducted as a double platform survey and mark recapture distance sampling techniques were used to correct for perception bias which resulted in an estimate of 4,468 whales (95% CI 1,343–14,871). Both estimates are negatively biased because no corrections were applied for whales that were submerged during the passage of the survey plane. The abundance estimate furthermore only represents the coastal areas of West Greenland. The sightings at the westernmost border of the strata suggest that the entire Baffin Bay-Davis Strait summer abundance of fin whales could be considerably larger. Based on comparison with previous surveys in West Greenland in 1987/88 and 2005 it appears that the fin whale abundance in West Greenland has increased.

Micro-Climate Computed Machine and Deep Learning Models for Prediction of Surface Water Temperature Using Satellite Data in Mundan Water Reservoir

Water temperature is an important indicator of water quality for surface water resources because it impacts solubility of dissolved gases in water, affects metabolic rates of aquatic inhabitants, such as fish and harmful algal blooms (HABs), and determines the fate of water resident biogeochemical nutrients. Furthermore, global warming is causing a widespread rise in temperature levels in water sources on a global scale, threatening clean drinking water supplies. Therefore, it is key to increase the frequency of spatio-monitoring for surface water temperature (SWT). However, there is a lack of comprehensive SWT monitoring datasets because current methods for monitoring SWT are costly, time consuming, and not standardized. The research objective of this study was to estimate SWT using data from the Landsat-8 (L8) and Sentinel-3 (S3) satellites. To do this, we used machine learning techniques, such as Support Vector Regression (SVR), Gaussian Process Regression (GPR), simple neural network (ANN), and deep learning techniques (Long Short Term Memory, LSTM, and Convolutional Long Short Term Memory, 1D ConvLSTM). Using deep and machine learning techniques to regress satellite data to estimate SWT presents a number of challenges, including prediction uncertainty, over- or under-estimation of measured values, and significant variation in the final estimated data. The performance of the L8 ConvLSTM model was superior to all other methods (R2 of 0.93 RMSE of 0.16 °C, and bias of 0.01 °C). The factors that had a significant effect on the model’s accuracy performance were identified and quantified using a two-factor analysis of variance (ANOVA) analysis. The results demonstrate that the main effects and interaction of the type of machine/deep learning (ML/DL) model and the type of satellite have statistically significant effects on the performances of the different models. The test statistics are as follows: (satellite type main effect p *** ≤ 0.05, Ftest = 15.4478), (type of ML/DL main effect p *** ≤ 0.05, Ftest = 17.4607) and (interaction, satellite type × type of ML/DL p ** ≤ 0.05, Ftest = 3.5325), respectively. The models were successfully deployed to enable satellite remote sensing monitoring of SWT for the reservoir, which will help to resolve the limitations of the conventional sampling and laboratory techniques.

A hybrid modelling framework of machine learning and extreme value theory for crash risk estimation using traffic conflicts

Extreme value theory is the state-of-the-art modelling technique for estimating crash risk from traffic conflicts, with two different sampling techniques, i.e. block maxima and peak-over-threshold, at its core. However, the uncertainty associated with the estimates obtained by these sampling techniques has been too large to enable its widespread practical use. A fundamental reason for this issue is the improper selection of extreme values and a lack of a suitable and efficient sampling mechanism. This study proposes a hybrid modelling framework of machine learning and extreme value theory to estimate crash risk from traffic conflicts with an efficient sampling technique for identifying extremes. More specifically, a machine learning approach replaces the conventional sampling techniques with anomaly detection techniques since an anomaly is a data point that does not conform with the rest of the data, making it very similar to the definition of an extreme value. Six representative machine learning-based unsupervised anomaly detection algorithms have been tested in this study. They include iforest, minimum covariance determinant, one-class support vector machine, k-nearest neighbours, local outlier factor, and connectivity-based outlier factor. The extremes identified by these algorithms are then fitted to extreme value distributions for both univariate and bivariate frameworks. These algorithms were tested on a large set of traffic conflict data collected for four weekdays (6 am to 6 pm) from three four-legged intersections in Brisbane, Australia. Results indicate that the proposed hybrid models consistently outperform the conventional extreme value models, which use block maxima and peak-over-threshold as the underlying sampling technique. Among the sampling algorithms, iforest has been found to perform better than other algorithms in estimating crash risks from traffic conflicts. The proposed hybrid modelling framework represents a methodological advancement in traffic conflict-based crash estimation models and opens new avenues for exploring the possibility of utilising machine learning techniques within the existing traffic conflict techniques.

Applications of cryobiopsy in airway, pleural, and parenchymal disease

Introduction :Cryobiopsy is a novel diagnostic technique for thoracic diseases which has been extensively investigated over the past 20 years. It was originally proposed for the diagnosis of endobronchial lesions and diffuse parenchymal lung disease due to limitations of conventional sampling techniques including small size and presence of artifacts. Areas covered :We will review recent evidence related to the expanding use of cryobiopsy in thoracic diseases. To identify references, the MEDLINE database was searched from database inception until May 2022 for case series, cohort studies, randomized controlled trials, systematic reviews and meta-analyses related to cryobiopsy. Expert opinion Cryobiopsy has expanding applications in the field of thoracic diseases. Evidence to support transbronchial cryobiopsy as an alternative to surgical lung biopsy is increasing and was recently endorsed as a conditional recommendation by the latest American Thoracic Society guideline update for Idiopathic Pulmonary Fibrosis. Developments in technology and technique, in particular the availability of a 1.1 mm flexible cryoprobe, have extended applications to pulmonary diseases, including diagnosis of interstitial lung diseases, peripheral pulmonary lesions, and lung transplant rejection.