Standard Methods Research Articles

DEVELOPMENT OF A ROBOTIC FABRICATION SYSTEM FOR CEMENTITIOUS MATERIALS

Our team at Klokner Institute under Czech Technical University in Prague is working in a joint effort with Technical University of Liberec and Klokner on a comprehensive 3D printing system for cementitious materials, including specially optimized robotic arm. The goal of this system is to decrease the environmental impact of construction industry by reducing the volume of materials and time required, as well as reducing need for human labor. 3D printing also makes possible to build complex functional shapes, that would be too complicated or prohibitively expensive to manufacture using standard industry methods. Combining expertise of these two institutions lead to development of a robust system, that seamlessly integrates in-house developed mechanics and print material. One of key areas of our research is also testing mechanical properties of printed parts which is essential to safely integrate this construction method in real-world use in the future.

Isbijab – a new centre for the development of Islamic law (XI-XII)

The relevance of this article covers historical, religious, local and diplomatic factors, which reflect the importance of research and the multifaceted nature of Isbijab. The purpose is to study the Isbijab School of fiqh law in the Middle Ages in the context of Islamic law and the history of Kazakhstan. In this work, standard historiographical methods are used: historical-systemic method, historical-comparative method, method of historical periodization and others. The main result is to clarify the role of the fiqh school of Isbijab in the context of studying the history of Islamic law on the territory of modern Kazakhstan and in the region as a whole. The authors also found that Isbijab was one of the centres of Islamic studies and law not only in Kazakhstan but also in the whole of Central Asia in the XI to XII centuries. It was the time when Isbijab developed its legal concept and school of fiqh, the Hanafi madhhab. This school of Islamic law introduced a new generation of legal scholars and their pupils, whose major works and academic degrees paved their way in the historiography. Their experience helped the researchers to study the manuscript works of medieval Isbijab jurists from a historical-legal and theological point of view. The paper shows the findings of an ongoing study of Isbijab legal practitioners in the framework of the "Mukhtasar al-Tahawi" book. Work has practical relevance not only in the context of Islamic studies and Islamic law but also in history, international relations, country knowledge and in other disciplines.

HybridTransferNet: soil image classification through comprehensive evaluation for crop suggestion

<p>Soil image classification is a critical task within the realms of agriculture and environmental applications. In recent years, the integration of deep learning has sparked significant interest in image-based soil classification. Transfer learning, a well-established technique in image classification, involves finetuning a pre-trained model on a specific dataset. However, conventional transfer learning methods typically focus solely on fine-tuning the final layer of the pre-trained model, which may not suffice to attain high performance on a new task. HybridTransferNet, a unique hybrid transfer learning approach designed for soil classification based on images is proposed in this paper. HybridTransferNet goes beyond the conventional approach by finetuning not only the final layer but also a select number of earlier layers in a pre-trained ResNet50 model. This extension results in substantially enhanced ability to classify when compared to standard transfer learning methods. Our evaluation of HybridTransferNet, conducted on a soil classification dataset, encompasses the reporting of various performance indicators, such as the F1 score, recall, accuracy, and precision. Our findings from experiments highlight HybridTransferNet's advantages over conventional transfer learning strategies, establishing it as a state-of-the-art solution in the domain of soil classification.</p>

Exploring solute binding proteins in Pseudomonas aeruginosa that bind to γ-aminobutyrate and 5-aminovalerate and their role in activating sensor kinases.

The standard method of receptor activation involves the binding of signals or signal-loaded solute binding proteins (SBPs) to sensor domains. Many sensor histidine kinases (SHKs), which are activated by SBP binding, are encoded adjacent to their corresponding sbp gene. We examined three SBPs of Pseudomonas aeruginosa PAO1, encoded near the genes for the AgtS (PA0600) and AruS (PA4982) SHKs, to determine how common this arrangement is. Ligand screening and microcalorimetric studies revealed that the SBPs PA0602 and PA4985 preferentially bind to GABA (KD = 2.3 and 0.58 μM, respectively), followed by 5-aminovalerate (KD = 30 and 1.6 μM, respectively) and ethanoldiamine (KD = 2.3 and 0.58 μM, respectively). In contrast, AgtB (PA0604) exclusively recognizes 5-aminovaleric acid (KD = 2.9 μM). However, microcalorimetric titrations did not show any binding between the AgtS sensor domain and AgtB or PA0602, regardless of the presence of ligands. Similarly, bacterial two-hybrid assays did not demonstrate an interaction between PA4985 and the AruS sensor domain. Therefore, sbp and shk genes located nearby are not always functionally linked. We previously identified PA0222 as a GABA-specific SBP. The presence of three SBPs for GABA may be linked to GABA's role as a trigger for P. aeruginosa virulence.

AI Driven Lab-on-chip Cartridge for Automated Urinalysis

After haematology, urinalysis is the most common biological test performed in clinical settings. Hence, simplified workflow and automated analysis of urine elements are of absolute necessities. In the present work, a novel lab-on-chip cartridge (Gravity Sedimentation Cartridge) for the auto analysis of urine elements is developed. The GSC consists of a capillary chamber that uptakes a raw urine sample by capillary force and performs particles and cells enrichment within 5 min through a gravity sedimentation process for the microscopic examination. Centrifugation, which is necessary for enrichment in the conventional method, was circumvented in this approach. The AI100 device (Image based autoanalyzer) captures microscopic images from the cartridge at 40x magnification and uploads them into the cloud. Further, these images were auto-analyzed using an AI-based object detection model, which delivers the reports. These reports were available for expert review on a web-based platform that enables evidence-based tele reporting. A comparative analysis was carried out for various analytical parameters of the data generated through GSC (manual microscopy, tele reporting, and AI model) with the gold standard method. The presented approach makes it a viable product for automated urinalysis in point-of-care and large-scale settings.

CellSNAP: a fast, accurate algorithm for 3D cell segmentation in quantitative phase imaging.

Three-dimensional quantitative phase imaging (QPI) has rapidly emerged as a complementary tool to fluorescence imaging, as it provides an objective measure of cell morphology and dynamics, free of variability due to contrast agents. It has opened up new directions of investigation by providing systematic and correlative analysis of various cellular parameters without limitations of photobleaching and phototoxicity. While current QPI systems allow the rapid acquisition of tomographic images, the pipeline to analyze these raw three-dimensional (3D) tomograms is not well-developed. We focus on a critical, yet often underappreciated, step of the analysis pipeline that of 3D cell segmentation from the acquired tomograms. We report the CellSNAP (Cell Segmentation via Novel Algorithm for Phase Imaging) algorithm for the 3D segmentation of QPI images. The cell segmentation algorithm mimics the gemstone extraction process, initiating with a coarse 3D extrusion from a two-dimensional (2D) segmented mask to outline the cell structure. A 2D image is generated, and a segmentation algorithm identifies the boundary in the plane. Leveraging cell continuity in consecutive -stacks, a refined 3D segmentation, akin to fine chiseling in gemstone carving, completes the process. The CellSNAP algorithm outstrips the current gold standard in terms of speed, robustness, and implementation, achieving cell segmentation under 2s per cell on a single-core processor. The implementation of CellSNAP can easily be parallelized on a multi-core system for further speed improvements. For the cases where segmentation is possible with the existing standard method, our algorithm displays an average difference of 5% for dry mass and 8% for volume measurements. We also show that CellSNAP can handle challenging image datasets where cells are clumped and marred by interferogram drifts, which pose major difficulties for all QPI-focused AI-based segmentation tools. Our proposed method is less memory intensive and significantly faster than existing methods. The method can be easily implemented on a student laptop. Since the approach is rule-based, there is no need to collect a lot of imaging data and manually annotate them to perform machine learning based training of the model. We envision our work will lead to broader adoption of QPI imaging for high-throughput analysis, which has, in part, been stymied by a lack of suitable image segmentation tools.

Calculating daily dose in the Observational Medical Outcomes Partnership Common Data Model.

We aimed to develop a standardized method to calculate daily dose (i.e., the amount of drug a patient was exposed to per day) of any drug on a global scale using only drug information of typical observational data in the Observational Medical Outcomes Partnership Common Data Model (OMOP CDM) and a single reference table from Observational Health Data Sciences And Informatics (OHDSI). The OMOP DRUG_STRENGTH reference table contains information on the strength or concentration of drugs, whereas the OMOP DRUG_EXPOSURE table contains information on patients' drug prescriptions or dispensations/claims. Based on DRUG_EXPOSURE data from the primary care databases Clinical Practice Research Datalink GOLD (United Kingdom) and Integrated Primary Care Information (IPCI, The Netherlands) and healthcare claims from PharMetrics® Plus for Academics (USA), we developed four formulas to calculate daily dose given different DRUG_STRENGTH reference table information. We tested the dose formulas by comparing the calculated median daily dose to the World Health Organization (WHO) Defined Daily Dose (DDD) for six different ingredients in those three databases and additional four international databases representing a variety of healthcare settings: MAITT (Estonia, healthcare claims and discharge summaries), IQVIA Disease Analyzer Germany (outpatient data), IQVIA Longitudinal Patient Database Belgium (outpatient data), and IMASIS Parc Salut (Spain, hospital data). Finally, in each database, we assessed the proportion of drug records for which daily dose calculations were possible using the suggested formulas. Applying the dose formulas, we obtained median daily doses that generally matched the WHO DDD definitions. Our dose formulas were applicable to >85% of drug records in all but one of the assessed databases. We have established and implemented a standardized daily dose calculation in OMOP CDM providing reliable and reproducible results.

Safety of cholecystectomy performed by surgeons who prefer fundus first versus surgeons who prefer a standard laparoscopic approach

BackgroundAn alternative method to standard laparoscopic cholecystectomy (SLC) is the “fundus first” method (FFLC). Concerns have been raised that FFLC can lead to misinterpretation of important anatomical structures, thus causing complications of a more serious kind than SLC. Comparisons between the methods are complicated by the fact that FFLC is often used as a rescue procedure in complicated cases. To avoid confounding related to this we conducted a population-based study with comparisons on the surgeon level. MethodIn GallRiks, the Swedish registry for Gallbladder surgery, we stratified all cholecystectomies performed 2006–2020 in three groups: surgeries carried out by surgeons that uses FFLC in <20 % of the cases (N = 150,119), in 20–79 % of the cases (N = 10,212) and in 80 % or more of the cases (N = 3176). We compared the groups with logistic regression, adjusting for sex, age, surgical experience, year of surgery and history of acute cholecystitis. All surgical complications (bleeding, gallbladder perforation, visceral perforation, infection, and bile duct injury) were included as outcome. A separate analysis was done with regards to operation time. ResultsNo difference in incidence of all surgical complications or bile duct injury were seen between groups. The rates of bleeding (OR 0.34 [0.14–0.86]) and gallbladder perforation (OR 0.61 [0.45–0.82]) were significantly lower in the “fundus first > 80% group” and the operative time was shorter (OR 0.76 [0.69–0.83]). ConclusionIn this study including >160,000 cholecystectomies, both methods was found to be equally safe. Key messageDuring laparoscopic cholecystectomy, the standard method of dissection and fundus first dissection are equally safe surgical techniques. Surgeons need to learn both methods to be able to use the one most appropriate for each individual case.

A method for determining groups in cumulative incidence curves in competing risk data.

The cumulative incidence function is the standard method for estimating the marginal probability of a given event in the presence of competing risks. One basic but important goal in the analysis of competing risk data is the comparison of these curves, for which limited literature exists. We proposed a new procedure that lets us not only test the equality of these curves but also group them if they are not equal. The proposed method allows determining the composition of the groups as well as an automatic selection of their number. Simulation studies show the good numerical behavior of the proposed methods for finite sample size. The applicability of the proposed method is illustrated using real data.

Development of Real-time PCR Method for Detection of Xanthomonas campestris pv. juglandis Causing Walnut Bacterial Blight

Walnut is one of the important economic tree species in the world. For the past few years, with the continuous expansion of walnut planting area, walnut bacterial blight caused by Xanthomonas campestrispv. juglandis has critically affected walnut production and caused economic losses. In this research, by comparing the gene sequences of X. campestrispv. juglandis and its closely related bacterial species, the 16S rDNA gene sequence was selected, and the specific primers were evaluated using PCR. Subsequently, the real-time fluorescence PCR specific detection method of X. campestrispv. juglandis was established and optimized. The specificity of real-time PCR was verified for 23 strains isolated from walnut and its surrounding soil, including eight target pathogens. The specific amplification was possible even when the cDNA template concentration was 7.0×10-5 µg/mL, hence, the detection sensitivity of the standard method is 7.0×10-5 µg/mL. The reliability of the established real-time PCR detection method in field detection was verified by the identification of target bacteria in 8 randomly collected healthy leaves and leaves of suspected walnut blight. This method laid a foundation for the early diagnosis of X. campestrispv. juglandis.

Assessment of the nutritional quality of weaning food prepared from fermented blends of sorghum (Ogi) and soybean

This study investigated the nutritional quality of weaning food prepared from fermented blends of sorghum (ogi) and soybean. The raw samples were processed into flour and were mixed in ratio of 60:40 and 70:30 respectively. Lactic acid bacteria (LAB) were isolated from fermented ogi and were accessed for their technological properties. The pH and total titratable acidity of the ogi was accessed, proximate composition and shelf-life of the weaning blends were determined by standard methods. A total of 10 LAB isolates were obtained, characterized and identified as L. plantarum (50%), L. fermentum (30%), L. delbrueckii (10%), and L. brevi (10%). Lactic acid, diacetyl and hydrogen peroxide produced by the LAB isolates ranged from 1.203 ± 0.006 - 3.410 ± 0.010, 1.21 ± 0.02 - 3.63 ± 0.05 and 0.650 ± 0.060 - 1.910 ± 0.040 (mg/mL) respectively. The fermentation of the ogi resulted in pH reduction from 4.5 ± 0.01- 2.40 ± 0.01 and increased titratable acidity 12.49 ± 0.01 - 23.00±0.01 g/L. The 60:40 weaning blend of sorghum ogi flour and soybean improved protein, ash, crude fiber, moisture, fat, vitamin A, ascorbic acid, riboflavin, and beta carotene content compared to a 70:30 blend. The blend also showed improvements in mineral content, with a significantly higher overall nutritional value compared to the 70:30 blend. Coliforms were not observed during the shelf-life monitoring. This study concluded that these blends meet daily nutritional requirements, provide health benefits, and meet recommended standards for weaning.

Assessment of microbial properties, and heavy metals contents of surface water and ground water samples In Ureje and Ireje, Ekiti State, Nigeria.

Water is everywhere, · it is the most basic and necessary element of life, as well as the most important and abundant compound in the ecosystem. Standard methods were used to evaluate the physicochemical properties, microbial properties, and heavy metal content of river and well water samples in Ekiti State, South-West Nigeria. Important parameter like pH, electrical conductivity, total dissolved solids, DO, BOD, turbidity, total alkalinity, total hardness, heavy metals and microbial properties are determined. The research work indicated that temperature, odour, pH, alkalinity, TDS, biochemical oxygen demand, DO, chloride, nitrate and turbidity were within the range of WHO permissible limits for drinking water while color, Conductivity, iron and manganese were above the WHO permissible limits. The study also indicated that the microbial contents such as total viable count, yeast/mold and coliform were above the WHO permissible limits for drinking. These results show that the water sources were slightly contaminated and unsafe for human consumption. This water must be treated before it may be consumed or used for domestic application.

Off-label use of tramadol combined with Lacasera® soft drink: A sub-acute toxicological study using Wistar rats to evaluate the effects of combination on human basic haematological parameters and weight changes

Tramadol is a synthetic opioid that is used to treat moderate to severe pain in both acute and chronic conditions. Tramadol is predominantly used off-label for premature ejaculation and euphoria among male youth in Nigeria, especially when dissolved in Lacasera® soft drink, which gives it a pleasant taste. Research has not yet examined the effects of this combination on hematological parameters, despite the fact that this type of abuse is common among young people and poses a public health risk. A 28-day subacute study was conducted with Wistar rats weighing 160-180g. The rats were separated into 8 groups of 6 each. The control groups: 1 and 2 were treated with Lacasera® and deionized water respectively. Groups 3, 4 and 5 received 35mg/kg per day, 70.7mg/kg per day and 106mg/kg per day of Tramadol dissolved in deionized water respectively. Groups 6, 7 and 8 received similar doses of Tramadol dissolved in Lacasera®. Blood samples were analyzed using auto-analyzer and standard methods. The data was analyzed using a statistical tool software (SPSS version 27). All results were presented as mean ± SD. Values were considered significant at p&lt;0.05. Hematological analysis of groups treated with Lacasera®-Tramadol combination shows dose-dependent significant decreases (p&lt;0.05) in PCVs, RBCs, and Hbs. WBCs and platelets increased in groups that received Lacasera®-Tramadol combination. The study concludes that regular or infrequent users of Lacasera® without Tramadol are unlikely to experience serious hematological complications. However, chronic Tramadol-Lacasera® users will experience increased toxicity over time, leading to hemolytic anemia.

Granulicatella adiacens: An uncommon pathogen in prosthetic joint infections

Granulicatella adiacens is an uncommon culprit in prosthetic joint infections, especially when predisposing factors are absent. Here, we present the case of a 78-year-old female who developed an acute surgical site infection shortly after undergoing left total knee arthroplasty. Despite initial negative cultures, subsequent analysis identified Granulicatella adiacens in the knee fluid, marking only the second reported instance in the United States and the seventh globally. This singular case highlights the considerable challenges associated with isolating this organism, emphasizing its atypical presentation and diagnostic elusiveness. Typically associated with endocarditis and bacteremia, its involvement in isolated surgical site infections is particularly unusual. Our case underscores the necessity for heightened clinical suspicion and the adoption of specialized diagnostic methodologies to accurately detect Granulicatella adiacens infections. Given its fastidious nature and nutritional requirements, standard culture methods may fail to identify this pathogen, necessitating alternative diagnostic approaches. As such, the utilization of specialized media becomes paramount in clinical diagnostics to facilitate appropriate management and optimize healthcare resource allocation. By enhancing our ability to detect and treat infections caused by Granulicatella adiacens, we can mitigate patient morbidity and reduce the burden of unnecessary interventions, thereby improving patient outcomes and healthcare efficiency.

Assessment of biogas production potentials of palm oil mill effluent and cow dung substrates in anaerobic digester

The biogas production potentials of palm oil mill effluent (POME) and cow manure (CM) substrates were evaluated using anaerobic digester. The first two digesters (D1 and D2) were charged with POME and CM for mono-digestion respectively. However, co-substrates digestion was done in digesters D3 (60/40 % POME-CM), D4 (70/30 % POME-CM), and D5 (80/20 % POME-CM) and all the digestion lasted for 21 days. The biogas yield of the digesters and performance of the digestions were measured by the analysis of moisture content, pH, total suspended solids (TSS), total solids (TS), volatile solid (VS), chemical oxygen demand (COD), biochemical oxygen demand (BOD) and total organic carbon (TOC) using standard analytical methods. The results showed that D4 (70/30 % POME-CM) has the highest biogas yield (1875±0.11 mL) while D2 (100 % CM) gave the lowest biogas yield (443±0.15 mL). The BOD of D3, D4 and D5 were not detected. The concentrations of COD, TS, TSS and TOC showed a significant (p&lt;0.05) decrease in D1, D3, D4 and D5 compared to D2. While D2, D3, D4 and D5 showed a significant (p&lt;0.05) decrease in moisture content compared to D1. However, D1, D3, D4 and D5 showed increasing level of alkalinity compared to acidic level of D2. Therefore, this study suggests that co-substrates anaerobic digestion of palm oil mill effluent and CM are suitable for biogas production.

Antibiotic resistance and plasmid profile of bacteria associated with nosocomial infections: A case study of Ekiti -State Teaching Hospital

Many serious health problems resulting in an enormous burden of morbidity and high health care costs are traceable to infections caused by the nosocomial pathogens; major victims are relatives of patients, the care givers who are doing their legal duties and at times the patients whose conditions could be complicated. The causative organisms of these infections and their sensitivity to antibiotics need to be ascertained. This study investigated the antibiotic sensitivity and plasmid profile of bacteria associated with nosocomial infections. A total of 45 samples were collected from children, male and female surgical wards in Ekiti State Teaching Hospital, Ado-Ekiti by using swab sticks and settling plates method. Isolation of bacteria, antibiotic sensitivity and plasmid profiling of the isolates were carried out using standard microbiological methods. The results showed that a total of 56 bacterial isolates were obtained from the 3 different wards, this includes Staphylococcus aureus, Staphylococcus epidermidis, Escherichia coli, Lactobacillus fermenti, Bacillus subtilis, Bacillus cereus and Micrococcus luteus. Staphylococcus aureus had the highest frequency of occurrence with 30(53.6%), followed by Staphylococcus epidermidis 10(17.7%), Escherichia coli 7(12.5%), Lactobacillus fermentii and Micrococcus luteus 3(5.4%) and Bacillus subtilis 2(3.6%) respectively, while Bacillus cereus 1(1.8%) had the least frequency of occurrence. The gram positive isolates were more resistant to the antibiotics compare to the gram negative isolates, Staphylococcus aureus was the most resistant of all the isolates followed by Staphylococcus epidermidis, the five representative resistant isolates harbored plasmid of different sizes. The findings of this study suggests that patients, care givers and visitors to the hospital should maintain good personal hygiene and proper sanitary measures to avoid nosocomial infections, therefore, surveillance of nosocomial pathogens is important to reduce hospital stay, cost, morbidity and mortality rate.

Improvement of optical wave propagation simulations: the scaled angular spectrum method for far-field and focal analysis

In the field of optics, accurately simulating wave propagation is essential for both theoretical insights and practical applications. This study introduces the scaled angular spectrum method (Sc-ASM) for simulating far-field and focal patterns, overcoming the limitations inherent in the standard angular spectrum method (ASM) by allowing variable sampling intervals between source and observation planes. Comparative analysis with the Rayleigh–Sommerfeld integral demonstrates Sc-ASM's superior accuracy in estimating the far-field patterns of beams with complex phase structures. Our results underscore Sc-ASM’s potential to set a new benchmark in optical simulations, significantly advancing optical system design and the study of wave propagation.

On the capacity of artificial intelligence techniques and statistical methods to deal with low-quality data in medical supply chain environments

We illustrate the capacity of Artificial Intelligence (AI) and Machine Learning (ML) techniques to preserve consistent categorization abilities whenever the quality of the data decreases, displaying mistakes or mismatches across matrix entries, while standard statistical methods exhibit significant modifications in the value of the corresponding coefficients. We design algorithms of different complexity to generate a series of comparable profiles. These profiles are compared within environments that allow for an immediate identification of the generating algorithms and within increasingly complex settings involving almost identical profiles derived from different algorithms. AI and ML techniques outperform standard statistical methods when distinguishing the algorithms generating the profiles. Building on these results, we perform a retrospective analysis where AI and ML techniques are applied to two empirical scenarios defined by different data series of patients transplanted through the period 2006–2019. The first scenario contains the variables describing the evolution of patients inputted correctly. In the second, we modify the content of the vectors of characteristics defining the evolution of patients by exchanging the values of a subset of realizations from two categorical variables. AI and ML techniques are consistently accurate when categorizing patients correctly within both scenarios, a feature particularly relevant when the quality of the information sources composing the medical chain varies. This latter problem is exacerbated among hospitals located in developing countries, where the quality of the data gathered limits their identification and extrapolation capacities.

A Framework for Solving Parabolic Partial Differential Equations on Discrete Domains

We introduce a framework for solving a class of parabolic partial differential equations on triangle mesh surfaces, including the Hamilton-Jacobi equation and the Fokker-Planck equation. PDE in this class often have nonlinear or stiff terms that cannot be resolved with standard methods on curved triangle meshes. To address this challenge, we leverage a splitting integrator combined with a convex optimization step to solve these PDE. Our machinery can be used to compute entropic approximation of optimal transport distances on geometric domains, overcoming the numerical limitations of the state-of-the-art method. In addition, we demonstrate the versatility of our method on a number of linear and nonlinear PDE that appear in diffusion and front propagation tasks in geometry processing.

A review of the environments, biota, and methods used in microplastics research in South Africa

Microplastics are small plastic materials often defined as those between 5 mm and 0.05 mm in size. Microplastics can have toxicological impacts on various biota, from gut blockages to the transport or leaching of toxicants used in their production or absorbed from the surrounding environment. Although microplastic research has increased significantly, microplastic research in Africa lags behind that of developed countries. South Africa is the African nation with the highest number of microplastic publications. We aimed to determine the current state of microplastic research in South Africa. A total of 46 publications on microplastics in South Africa have been produced. However, many of these publications use methods that might not be accurate in determining holistic descriptions of microplastics in the aquatic environment. Similarly, many ecologically relevant environments and species have not been investigated for microplastics in the country, including any atmospheric or terrestrial environment. We conclude that, although the research being produced in South Africa can be considered adequate, a singular standard method for sampling and assessing microplastics in South African environments is required. The production of such a standard method would be critical to use as a monitoring tool to determine and compare microplastic abundances across the country and globally.