Laboratory Methods Research Articles

Quantification of mycophenolic acid in plasma by isotope dilution liquid chromatography-tandem mass spectrometry candidate reference method.

Accurate measurements of plasma mycophenolic acid (MPA) are essential for therapeutic drug monitoring in transplant recipients and autoimmune diseases. The performance of plasma mycophenolic acid routine methods remains highly variable that calls for a candidate reference measurement procedure (cRMP) to improve the standardization of plasma mycophenolic acid measurements. In this study, sample preparation was based on protein precipitation with methanol followed by further dilution. The mycophenolic acid was quantified by the isotope dilution liquid chromatography-tandem mass spectrometry (ID-LC-MS/MS) with electrospray ionization in positive ion mode. According to the Clinical and Laboratory Standards Institute (CLSI) documents C62-A and C50-A, the basic analytical performance of the candidate reference method was verified, such as linearity, limit of quantification, matrix effect, precision, accuracy, and uncertainty. Moreover, the candidate reference measurement procedure was compared with the routine liquid chromatography-tandem mass spectrometry (LC-MS/MS) method in a clinical laboratory. Based on the data, the mycophenolic acid in human plasma was well detected by ID-LC-MS/MS. No apparent interferences were found with the mycophenolic acid measurement. The calibration curve for the mycophenolic acid was linear in the concentration range of 0.1-50μg/mL with a correlation coefficient of 0.9999 under the optimum experimental conditions. This method was sensitive because the low limit of quantitation (LOQ) was 0.05μg/mL. The recoveries of MPA were 98.11-98.95%. The intra-day and inter-day coefficients of variations (CV) of our method were ≤ 1.53% and ≤ 0.51%, respectively. No obvious matrix effect was observed. There was a good correlation between this method and the clinical routine LC-MS/MS method. To sum up, we established and validated a reliable plasma MPA method using ID-LC/MS/MS. The desirable accuracy and precision of this method enable it to serve as a promising cRMP to improve the standardization for plasma MPA routine measurements.

Soil organic carbon and related properties under conservation agriculture and contrasting conventional fields in Northern Malawi

Conservation agriculture (CA) is widely promoted as an agroecology-based approach for soil conservation. Several studies have focused on effects of CA on crop yields and soil moisture dynamics in sub-Saharan Africa, with limited focus on effects of CA on soil organic carbon (SOC) and associated fractions. We collected representative soil samples from 30 paired farms under CA and conventional tillage in Mzimba district, north of Malawi to determine effects of tillage and soil depth on soil physico-chemical properties, total SOC, and organic carbon fractions. Undisturbed soil cores were collected for bulk density measurements. Different SOC pools were determined using the soil fractionation method, while soil physico-chemical analyses were conducted using standard laboratory methods on disturbed soil samples. Soil organic carbon content ranged from 0.4-1.8% in CA plots. This was significantly larger than SOC contents of 0.4-1.5% measured under conventional tilled plots. Tillage type and soil depth had significant interaction effects on SOC. For example, larger contents of SOC were measured at depths of 0-10 cm compared to 10-30 cm under CA plots. Soil depth had significant effects on most soil properties compared to tillage. Examples include Heavy Particulate Organic Matter-Carbon (POM-C) fraction, Mineral Associated Organic Matter-Carbon (MAOM-C), nitrogen in MAOM fraction and nitrogen in the Light POM fractions. These were larger in the 0-10 cm soil depth than in the 10-30 cm soil depth. In contrast, tillage type only had significant effects on the Heavy POM-C and MAOM-C fractions, which were larger under CA than conventional tilled plots. Conservation agriculture showed capacity to improve total SOC and its associated fractions, a finding relevant towards understanding effects of land management on carbon storage. However, challenges of competing residue use as feed, mulch, and fuel continue to impede mulching under CA systems. Longer term studies and use of alternative mulching options could be employed to recognise noticeable changes in other SOC beneficial pools in fields under CA.

Laboratory Methods for the Measurement of Spray Characteristics of the Nozzles in UAV Sprayers: A Review

Laboratory Methods for the Measurement of Spray Characteristics of the Nozzles in UAV Sprayers: A Review

Diagnosis and treatment of somatoform disorder with gastroenterological symptoms

Somatic symptoms, under the guise of which mental disorders can be hidden, are a problem for patients, psychiatrists and doctors of other specialties who are faced with this in the first place. Anxiety for one’s health and subjectively experienced bodily sensations force the patient to repeatedly seek medical help, which can aggravate maladjustment and cause significant damage to resources, causing additional stress, closing a vicious circle. Purpose of the study: to analyze the clinical manifestations, problems of diagnosis and treatment of psychopathological disorders using the example of clinical observation of somatoform disorder in a young man with gastroenterological symptoms. Materials and methods: the patient’s diagnosis corresponded to ICD-10 code F45.3 Somatoform dysfunction of the autonomic nervous system. Clinical-anamnestic, clinical-psychopathological, laboratory and instrumental methods were used. This clinical case demonstrates certain difficulties in diagnosing and treating somatoform disorders due to the need to exclude somatic pathology, nonspecific and difficult to differentiate symptoms that are not subjectively realized by the patient, individual selection of therapy and low compliance with it, and the need for psychotherapeutic assistance.

Signal-off colorimetric and signal-on fluorometric dual-mode aptasensor for ultrasensitive detection of Salmonella Typhimurium using graphitic carbon nitride.

Food safety is severely burdened by the prevalence of foodborne pathogens and the diseases they cause, necessitating the development of rapid, easy-to-use, highly sensitive, and reliable detection methods. Here, a signal-off colorimetric and signal-on fluorometric dual-mode detection method for Salmonella Typhimurium (S. typhimurium) was developed based on its unique interaction with aptamer DNA and graphitic carbon nitride (GCN). In the absence of a target Salmonella species, 6-carboxyfluorescein (FAM)-labeled aptamers are adsorbed on the surface of GCN primarily via a π-π interaction, resulting in reduced fluorescence of FAM through GCN-mediated quenching as well as improved peroxidase-like activity of GCN to generate intense blue color through facilitated electrostatic attraction between the negatively charged aptamer and positively charged 3,3',5,5'-tetramethylbenzidine (TMB) substrate. The introduction of S. typhimurium to the sample solution causes the detachment of the aptamer from GCN due to its higher affinity for S. typhimurium than GCN, thereby rapidly reducing the colorimetric signal and recovering the fluorescence. We successfully determined the number of S. typhimurium using this method in a remarkably short duration (10-30min), highlighting its rapidity. The limit of detection values for S. typhimurium were as low as 8 and 3CFU/mL when using colorimetric and fluorometric methods, respectively. Moreover, this method can be used to detect S. typhimurium spiked in real vegetable extract and milk with high reproducibility and reliability. This method serves as a convenient route to the rapid, sensitive, selective, and reliable detection of pathogens from complex food samples, with the potential to replace conventional yet laborious methods currently in use.

Serologic diagnosis of Entamoeba histolytica infection based on the gradient-based digital immunoassay.

Entamoeba histolytica is a parasite that could cause severe amebiasis, an extremely contagious parasitic disease with critical clinical symptoms. Timely diagnosis and treatment of E. histolytica are crucial for preventing complications and fatalities. However, current methods for E. histolytica diagnosis still rely on traditional and laborious methods such as stool examinations and serological immunoassay. Those methods urgently need improved diagnostic sensitivity, diagnostic specificity, detection time, and diagnostic accuracy. Herein, we developed a rapid and accurate gradient-based digital immunoassay system for diagnosing E. histolytica. This method uses a homemade pre-coated recombinant Igl-C fragment with high binding affinity, designed, recombinantly expressed, and purified by our lab on a one-shot observation microfluidic chip to capture the disease biomarker, specific anti-Igl-C antibodies in the serum. The captured antibodies are detected by anti-human IgG-coated gold nanoparticles, forming a digital binding sandwich immunocomplex. After simple imaging processing, the number of gold nanoparticles bound to the reaction surface within the same field of view of the microscope image was analyzed. Then, it can be easily determined in about 15min whether specific anti-Igl-C antibodies are in the serum, allowing quicker identification of E. histolytica infection. The detection and diagnosis performance were confirmed by testing 25 clinical serum samples. The novel diagnostic method provided a digital immunoassay platform and has a strong potential to be a high-efficiency tool for the clinical diagnosis of E. histolytica infection with heightened diagnostic sensitivity and diagnostic specificity. It offers the potential for rapid point-of-care testing, facilitating prompt treatment initiation and improved patient outcomes in resource-limited healthcare settings, making it a valuable asset in the fight against amebiasis.

Financial Growth of Sport Industry in the Extreme Context: Evidence From Iran Under Economic Sanction and COVID‐19 Pandemic

ABSTRACTThe objective of this research is to shift the narrative toward the impact of international sanctions against Iran and the ongoing COVID‐19 pandemic on the financial growth of the sports industry. Employing Importance‐Performance Analysis (IPA), we delve into the diverse factors influencing the financial dynamics of the sports sector in Iran. After an extensive review of the research literature, we identify pivotal elements affecting the financial prosperity of the sports industry. Using expert opinions and the content validity index (CVI), we select 20 significant factors shaping the financial landscape of the sports industry in Iran. Subsequently, we evaluate the importance and performance of these identified factors, drawing insights from the perspectives of 12 sports economics experts and sports managers. Employing Decision‐making Trial and Evaluation Laboratory (DANP) and IPA methods, we analyze the interplay of these factors. The research outcomes underscore the pivotal role of international sanctions against Iran and the challenges posed by the COVID‐19 pandemic in influencing the financial growth of the sports industry. Noteworthy factors include the stability of sports club incomes, the commercialization of the sports industry, private sector investment in sports, and the allocation of sports expenses within government expenditures. These findings illuminate the nuanced relationship between external geopolitical factors and internal financial dynamics, shaping the trajectory of the sports industry's financial growth in Iran.

Etiopathogenetic programs aimed at preventing in children risk-associated diseases caused by exposure to adverse components in emissions from a large non-ferrous metallurgic production

Introduction. Non-ferrous metallurgy holds a specific place among various productions that create potential health risks due to environmental pollution. Total emissions from the branch enterprises into ambient air reach three million tons (aluminum, fluorine, nickel, manganese, benzo(a)pyrene, sulfur dioxide and trioxide, hydrocarbon, etc.) per year, which accounts for 18% of the total emissions from all stationary sources. Implementation of etiopathogenetic prevention programs is a promising trend in preventing in children actual diseases associated with poor quality of the environment. The aim of this study was to develop and substantiate technologies aimed at reducing incidence in children of risk-associated pathologies caused by exposure to emissions from a large non-ferrous metallurgic enterprise as well as assess their effectiveness. Materials and methods. We examined five hundred forty two children lived in close proximity to a large non-ferrous metallurgic enterprise and 149 children who lived on a reference territory. Both groups were comparable in terms of age, sex, lifestyle, and socioeconomic position. The examination program included general clinical, functional, laboratory, chemical-analytical and statistical research methods, mathematical modelling, and assessment of technology effectiveness. Results. Fluorine, aluminum, manganese, chromium and nickel compounds as well as benzo(a)pyrene were identified in ambient air on the observation territory, their levels reaching 1.20–10.96 of average annual MPL; ambient air on the reference territory conformed to safety standards. Blood levels of these chemicals, which are 1.4–5.0 times higher than the reference level, raise prevalence of diseases of respiratory, nervous, musculoskeletal, and endocrine systems and blood by 1.6–3.1 times. Pathomorphosis and pathology prevalence are determined by serous-catarrhal and immune-dependent inflammation with damage to airway epithelium and thyrocytes, deceleration of endochondral ossification and bone remodelling, impaired neuromediator synthesis and inhibited synaptic transmission, hemopoiesis suppression; impaired iron and iodine metabolism, imbalance in immune-competent cell sub-populations, specific sensitization and redox imbalance induced by chemical exposures. Limitations. The study was performed in 4–7 years children lived in an area influenced by a large non-ferrous metallurgic enterprise. Conclusion. Implementation of etiopathogenetic prevention programs decreases frequency of relapses by 3.8 times; prevents a growth in incidence rates; increases the number of children in health groups I and II (practically healthy and without any chronic diseases) by 17–39%; promotes recovery of functional and metabolic activity of critical organs and systems in 68–98% cases. It reduces costs associated with medication provision for children with risk-associated pathology by 34–60% and by 50–75% for children with high and medium risks. Another significant result 2.6–3.3 times shorter duration of temporary disability due to taking care of a sick child with a risk-associated disease; this period decreases 2.6–3.3 times in case of children with high and medium risks. Economic efficiency of these technologies amounts to 6.5 rubles per 1 spent ruble.

Investigating The Circadian Rhythm Signaling Pathway in HTLV-1 Pathogenesis Using Boolean Analysis.

The Human T-cell lymphotropic virus type 1 (HTLV-1), an oncogenic virus belonging to the Deltaretrovirus genus, expresses various proteins, including Tax and HBZ, which can affect many cellular pathways. In this study, we have investigated the role of the circadian rhythm signaling pathway, a key regulator of human health, in the pathogenesis of HTLV-1 using Boolean Network analysis and laboratory methods. After an extensive search of the circadian rhythm pathway, we analyzed the relationships between the genes of this pathway using the R programming language and the BoolNet package. Subsequently, we examined the impact of viral proteins on the cellular clock rhythm genes. Finally, we identified three genes, PER2, CRY1, and DEC1, as the main checkpoints from the attractors obtained. These three genes and two viral genes, Tax and HBZ, were quantitatively assessed on two groups of individuals, including ten asymptomatic carriers infected with HTLV-1 and ten healthy individuals using the qRT-PCR method. Our results showed that the expression level of PER2 and DEC1 genes was significantly higher in the asymptomatic carriers compared to the healthy control group. Also, we recorded positive correlations between PER2 and DEC1, CRY1 and DEC1, and negative correlations between HBZ and CRY1 and DEC1. In this study, we suggested that in asymptomatic carriers, the virus might try to induce a chronic infection by escaping from the immune system due to an alteration in circadian rhythm pathways. We also detected three promising genes in this pathway that could have therapeutic or diagnostic value in these individuals. However, this possibility requires further research in different periods, different groups (e.g., ATLL and HAM/TSP), and examining a more significant number of circadian rhythm genes.

Comparison of 2 point-of-care analyzers and the Eurolyser assay with an IDEXX reference laboratory method for measurement of symmetric dimethylarginine in dogs.

To determine the concordance of 2 point-of-care (POC) analyzers and 2 reference laboratories (RLs) for serum symmetric dimethylarginine (SDMA) analysis in dogs. We hypothesized that the Vcheck V200 POC, IDEXX Catalyst POC, and Eurolyser assays would have an acceptable agreement with the IDEXX RL SDMA results. This was a prospective study conducted between August 2019 and March 2023. Blood collected from dogs treated at a referral hospital underwent SDMA analysis by 2 POC analyzers (IDEXX Catalyst and Vcheck V200) and 2 RL methods (Eurolyser and IDEXX). Dogs with suspected or known renal disease were preferentially included later in the study. 75 samples were included in the final analysis. There was a difference in SDMA results obtained from Eurolyser assays but not IDEXX Catalyst POC and Vcheck V200 POC assay compared to IDEXX RL results. When applied to the International Renal Interest Society chronic kidney disease staging classification, there was almost perfect agreement between Eurolyser and Vcheck V200 POC SDMA compared to IDEXX RL SDMA. While there was a strong to excellent correlation between assays, the results obtained via each assay demonstrated that there may be significant bias and analytical variation affecting the results. However, this may have minimal effect when applied clinically. Analyzer and method-specific reference intervals should be established for SDMA analysis. There is preliminary evidence to support the use of Eurolyser and Vcheck V200 POC SDMA assays in the staging of canine chronic kidney disease.

Decision tree-based learning and laboratory data mining: an efficient approach to amebiasis testing

BackgroundAmebiasis represents a significant global health concern. This is especially evident in developing countries, where infections are more common. The primary diagnostic method in laboratories involves the microscopy of stool samples. However, this approach can sometimes result in the misinterpretation of amebiasis as other gastroenteritis (GE) conditions. The goal of the work is to produce a machine learning (ML) model that uses laboratory findings and demographic information to automatically predict amebiasis.MethodData extracted from Jordanian electronic medical records (EMR) between 2020 and 2022 comprised 763 amebic cases and 314 nonamebic cases. Patient demographics, clinical signs, microscopic diagnoses, and leukocyte counts were used to train eight decision tree algorithms and compare their accuracy of predictions. Feature ranking and correlation methods were implemented to enhance the accuracy of classifying amebiasis from other conditions.ResultsThe primary dependent variables distinguishing amebiasis include the percentage of neutrophils, mucus presence, and the counts of red blood cells (RBCs) and white blood cells (WBCs) in stool samples. Prediction accuracy and precision ranged from 92% to 94.6% when employing decision tree classifiers including decision tree (DT), random forest (RF), XGBoost, AdaBoost, and gradient boosting (GB). However, the optimized RF model demonstrated an area under the curve (AUC) of 98% for detecting amebiasis from laboratory data, utilizing only 300 estimators with a max depth of 20. This study highlights that amebiasis is a significant health concern in Jordan, responsible for 17.22% of all gastroenteritis episodes in this study. Male sex and age were associated with higher incidence of amebiasis (P = 0.014), with over 25% of cases occurring in infants and toddlers.ConclusionsThe application of ML to EMR can accurately predict amebiasis. This finding significantly contributes to the emerging use of ML as a decision support system in parasitic disease diagnosis.Graphical

P-294. The pathway to a decade of carbapenem-resistant Enterobacterales (CRE) : A 9-years experience in a teaching hospital in the Dominican Republic

Abstract Background WHO warns about carbapenem-resistant Enterobacterales (CRE) and carbapenemase production, posing challenges in hospitals owing to treatment failure and rapid dissemination. In order to design adequate infection control and prevention strategies and local treatment guidelines, it is important to characterize the prevalence of these isolates. We aimed to assess the frequency of CRE and carbapenemase production in hospitalized patients between October 2015- March 2024. Methods A retrospective, descriptive and longitudinal study was conducted including all patients with positive CRE cultures, from January 2015 to March 2024, in a 289-bed tertiary hospital in the Dominican Republic. A database of susceptible and resistant Enterobacterales isolates was obtained, reviewing electronic records for culture origin, microorganisms, and carbapenemase production. Annual CRE rates were calculated including all hospitalized patients with Enterobacterales isolates. Results The CRE rate over a 9-years period was 1.7% (83/4843). A slight decrease was observed from years 2015 to 2017, followed by the lowest CRE rate in 2018 (0.2%). 2020 reported an increase of 160% in the CRE rate when compared to 2019, peaking at 3.5% in 2022. The most common microorganisms isolated were Klebsiella spp. (42.6%; 43/101) and Enterobacter cloacae complex (33,7%; 34/101) while the most common carbapenemase produced was KPC (39.4%; 39/99) followed by MBL (21.2%; 21/99). Urine cultures were the most common samples to isolate CRE, but a shift in the trend was observed in 2020, with blood cultures becoming the most common source of CRE. Sequencing of a small sample as part of a previous study reported the presence of KPC2 and KPC3. Conclusion Despite being in a low resource country, infection prevention and control strategies have managed to limit the spread reported in other hospital settings in Latin America. The increase seen post pandemic emphasizes this importance. Although KPC is the most common carbapenemase type, NDM has been increasing, posing a major growing concern on treatment failure. Laboratory methods stand as a fundamental tool to understand the magnitude of dissemination, to elaborate clinical guidelines and improve diagnosis and patients outcomes. Disclosures Rita A. Rojas-Fermin, MD,FIDSA, Gilead: Advisor/Consultant|Pfizer: Advisor/Consultant|Pfizer: Honoraria

Rapid structural analysis of bacterial ribosomes in situ

Rapid structural analysis of purified proteins and their complexes has become increasingly common thanks to key methodological advances in cryo-electron microscopy (cryo-EM) and associated data processing software packages. In contrast, analogous structural analysis in cells via cryo-electron tomography (cryo-ET) remains challenging due to critical technical bottlenecks, including low-throughput sample preparation and imaging, and laborious data processing methods. Here, we describe a rapid in situ cryo-ET sample preparation and data analysis workflow that results in the routine determination of sub-nm resolution ribosomal structures. We apply this workflow to E. coli, producing a 5.8 Å structure of the 70S ribosome from cells in less than 10 days and facilitating the discovery of a minor population of 100S-like disomes. We envision our approach to be widely applicable to related bacterial samples.

Navigating Uncertainty: A Novel Framework for Assessing Barriers to Blockchain Adoption in Freeport Operations

Blockchain technology holds the potential to significantly enhance efficiency and safety in freeport operations. However, fully realising its benefits necessitates a thorough assessment of the obstacles hindering its applications, which often depends on expert opinions characterised by uncertainty and inconsistency. This issue remains inadequately addressed in the existing literature due to the limitations of currently employed methods. To address this gap, this study aims to develop a novel methodology for assessing blockchain adoption barriers in freeports. It makes methodological contributions by combining the Decision-Making Trial and Evaluation Laboratory (DEMATEL) and Bayesian Network (BN) methods to identify and quantify complex interrelationships between barriers and facilitate probabilistic predictions of barrier strength. The model is parameterised using the ranked nodes method to reduce the reliance on expert-assigned probabilities. Primary data on barriers’ causal relationships are collected from experts with interdisciplinary experience in blockchain and freeport operations, grounding the analysis in real-world insights. This study makes practical contributions by analysing the blockchain application within a new context (i.e., freeports) and presenting novel findings. Key managerial insights include identifying high investment costs as the most interactive barrier and lack of trust among stakeholders as the most essential barrier. Additionally, evaluating the overall impact of barriers enables targeted strategies for freeport policymakers.

The Diagnostic Assessment of Inherited Platelet Function Defects.

In this article, our goal is to offer an introduction and overview of the diagnostic approach to inherited platelet function defects (iPFDs) for clinicians and laboratory personnel who are beginning to engage in the field. We describe the most commonly used laboratory methods and propose a diagnostic four-step approach, wherein each stage requires a higher level of expertise and more specialized methods. It should be noted that our proposed approach differs from the ISTH Guidance on this topic in some points. The first step in the diagnostic approach of iPFD should be a thorough medical history and clinical examination. We strongly advocate for the use of a validated bleeding score like the ISTH-BAT (International Society on Thrombosis and Haemostasis Bleeding Assessment Tool). External factors like diet and medication have to be considered. The second step should rule out plasmatic bleeding disorders and von Willebrand disease. Once this has been accomplished, the third step consists of a thorough platelet investigation of platelet phenotype and function. Established methods consist of blood smear analysis by light microscopy, light transmission aggregometry, and flow cytometry. Additional techniques such as lumiaggregometry, immune fluorescence microscopy, and platelet-dependent thrombin generation help confirm and specify the diagnosis of iPFD. In the fourth and last step, genetic testing can confirm a diagnosis, reveal novel mutations, and allow to compare unclear genetics with lab results. If diagnosis cannot be established through this process, experimental methods such as electron microscopy can give insight into the underlying disease.

Prediction of mechanical properties of eco-friendly concrete using machine learning algorithms and partial dependence plot analysis

Rice husk ash concrete (RHAC) shows promise as a beneficial supplementary material in concrete. However, determining mechanical properties such as compressive strength (CS) and splitting tensile strength (STS) of RHAC through conventional lab-scale methods is laborious and time-consuming. In this research, seven important variables were selected as inputs to predict CS and STS using machine learning (ML) models, including Gaussian Process Regression (GPR), Random Forest Regression (RFR), and Decision Tree Regression (DTR) with grid search optimization. The result presented revealed that selected machine learning models provide well accuracy for CS and STS estimates. Among these, the DTR model demonstrated superior performance, with CS prediction R2, RMSE, MAE, and MAPE values of 0.964, 3.314, 2.225, and 5.068, at the testing stage respectively. For STS at the testing stage, DTR achieved R2 of 0.969, RMSE of 0.177, MAE of 0.1322, and MAPE of 3.413. GPR and RFR models also performed well, with R2 values of 0.9434 and 0.9530 for CS prediction. The partial dependence plot (PDP) analysis revealed the optimal mix design parameters for achieving the desired strength. These results offer valuable insights for sustainable construction, allowing engineers to efficiently predict and optimize material performance, reducing the reliance on time-consuming lab methods.

UJI ANALISIS KUALITATIF DAN KUANTITATIF KADAR VITAMIN C PADA SEDIAAN KOSMETIK LOTION YANG BEREDAR DI KAB. MAROS DENGAN METODE SPEKTROFOTOMETER Uv-Vis

Cosmetics are an inseparable part of women's lives in particular and are used every day. Lotions are widely used to moisturize the skin and to brighten the skin. Lotion can be used for all skin types for teenagers aged 15 years and over. Vitamin C has various benefits, including as an antioxidant against pollution, sun exposure, brightening the skin, delaying the effects of aging, and increasing collagen formation which makes the skin supple, smooth and bright. The aim of the research was to determine the vitamin C content in cosmetic lotions according to the standards/labels circulating in the Maros district. The research was carried out using qualitative analysis methods in the pharmaceutical chemistry analysis laboratory of STIKes Salewangang Maros where the samples were lotion cosmetic products containing vitamin C at kab. Maros as stated on the product packaging/label and analyzed using a Uv-Vis spectrophotometer. The results of the research obtained showed that all lotion cosmetic preparations contained vitamin C with different percentage levels for each concentration, where lotion samples that did not have a distribution permit obtained high levels of Vitamin C, while lotions that had a distribution permit showed high levels of Vitamin C. not excessive, so it is safe to use for a long time.

Evaluating the Acoustic Absorption of Modular Vegetation Systems: Laboratory and Field Assessments Using an Impedance Gun

Introducing vegetation is an effective strategy for improving air quality and mitigating the heat island effect. Green modules, which consist of modules that support substrates and various plant species, integrate these elements. This study analyzes the acoustic absorption properties of a specific green wall module using an impedance gun and the Scan and Paint method for laboratory and on-site measurements. The impedance gun method is effective for in situ analysis, offering advantages over standardized techniques for inhomogeneous samples. The sound absorption coefficient of the substrate and the effects of different plant species were measured. Key findings reveal that the substrate primarily influences sound absorption, with its coefficient increasing with frequency, similar to porous materials. Vegetation enhances the acoustic absorption of the substrate, depending on coverage and thickness, with 80–90% of absorption attributed to the substrate and 4–20% to vegetation. However, not all dense plant species improve absorption; some configurations may decrease it. Improvement correlates with substrate coverage and vegetation layer thickness, while the impact of plant morphology remains unclear. These findings confirm vegetation’s potential as an acoustic absorption tool in urban settings. Additionally, green walls can enhance acoustic comfort in indoor environments such as offices and schools by reducing reverberation. They also improve air quality and provide aesthetic appeal, making them a multifunctional solution for modern architecture.

Analysis of Crack‐Tip Field in Orthotropic Compact Tension Shear Specimens: The Role of Elastic Mode Mixity and T‐Stress

ABSTRACTThe analysis of mixed‐mode crack propagation mechanisms in anisotropic materials remains a pivotal research focus. Although the compact tension shear (CTS) test is a recommended laboratory method, the lack of solutions for anisotropic crack‐tip field parameters hinders accurate assessment of stress states and deformations during crack propagation. To address this gap, this study conducted a systematic finite element analysis (FEA) to compute the elastic mode mixity and T‐stress results. It is found that by adjusting the loading angle along with the initial crack length, CTS tests on orthotropic specimens can similarly achieve a broad spectrum of Me at the crack‐tip. Statistical analysis indicates that applying isotropic solutions to estimate orthotropic T‐stress can lead to average errors of 234.1%. Subsequently, crack‐tip fields were analyzed, with crack initiation angles predicted using the maximum tangential stress (MTS) criterion and plastic zone profiles determined based on Hill's yield criterion. Larger fracture process zones enhance T‐stress correction effects on crack initiation angles, with positive T intensifying crack deflection, while negative T reduces it. Additionally, T also significantly affects the plastic zone's shape and size, with patterns varying according to material orthotropy. A detailed multiparameter characterization of crack‐tip fields will enhance the use of the CTS test for assessing multiaxial strength and mixed‐mode fracture mechanisms in anisotropic materials.

Short-Wave Infrared Spectroscopy for On-Site Discrimination of Hazardous Mineral Fibers Using Machine Learning Techniques

Asbestos fibers are well-known carcinogens, and their rapid detection is critical for ensuring safety, protecting public health, and promoting environmental sustainability. In this work, short-wave infrared (SWIR) spectroscopy, combined with machine learning (ML), was evaluated as an environmentally friendly analytical approach for simultaneously distinguishing the asbestos type, asbestos-containing materials in various forms, asbestos-contaminated/-uncontaminated soil, and asbestos-contaminated/-uncontaminated cement, simultaneously. This approach offers a noninvasive and efficient alternative to traditional laboratory methods, aligning with sustainable practices by reducing hazardous waste generation and enabling in situ testing. Different chemometrics techniques were applied to discriminate the material classes. In more detail, partial least squares discriminant analysis (PLS-DA), principal component analysis-based discriminant analysis (PCA-DA), principal component analysis-based K-nearest neighbors classification (PCA-KNN), classification and regression trees (CART), and error-correcting output-coding support vector machine (ECOC SVM) classifiers were tested. The tested classifiers showed different performances in discriminating between the analyzed samples. CART and ECOC SVM performed best (RecallM and AccuracyM equal to 1.00), followed by PCA-KNN (RecallM of 0.98–1.00 and AccuracyM equal to 1.00). Poorer performances were obtained by PLS-DA (RecallM of 0.68–0.72 and AccuracyM equal to 0.95) and PCA-DA (RecallM of 0.66–0.70 and AccuracyM equal to 0.95). This research aligns with the United Nations’ Sustainable Development Goals (SDGs), particularly SDG 3 (Good Health and Well-Being), by enhancing human health protection through advanced asbestos detection methods, and SDG 12 (Responsible Consumption and Production), by promoting sustainable, low-waste testing methodologies.