Laboratory Methods Research Articles

Direct On-Chip Diagnostics of Streptococcus bovis/Streptococcus equinus Complex in Bovine Mastitis Using Bioinformatics-Driven Portable qPCR

This study introduces an innovative on-site diagnostic method for rapidly detecting the Streptococcus bovis/Streptococcus equinus complex (SBSEC), crucial for livestock health and food safety. Through a comprehensive genomic analysis of 206 genomes, this study identified genetic markers that improved classification and addressed misclassifications, particularly in genomes labeled S. equinus and S. lutetiensis. These markers were integrated into a portable quantitative polymerase chain reaction (qPCR) that can detect SBSEC species with high sensitivity (down to 101 or 100 colony-forming units/mL). The portable system featuring a flat chip and compact equipment allows immediate diagnosis within 30 min. The diagnostic method was validated in field conditions directly from cattle udders, farm environments, and dairy products. Among the 100 samples, 51 tested positive for bacteria associated with mastitis. The performance of this portable qPCR was comparable to laboratory methods, offering a reliable alternative to whole-genome sequencing for early detection in clinical, agricultural, and environmental settings.

Investigation of Liver Function Test Findings in COVID-19 Patients Considering the Disease Timeline

Background: Several lines of evidence suggest that SARS-CoV-2 infection impacts liver function; however, the evaluation of these changes over time according to the disease timeline remains unclear. Objectives: The objective of this study was to identify potential alterations in liver function parameters during the first to fifth waves of COVID-19 and compare these alterations with the demographic and clinical outcomes of patients across the waves. Methods: This cross-sectional study included 1501 hospitalized patients with a confirmed RT-PCR diagnosis of COVID-19, referred to Shahid Sadoughi Hospital, Yazd, Iran, between November 20, 2019, and November 20, 2021. Liver function parameters, including alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP), total bilirubin, direct bilirubin, and albumin, were assessed using standard clinical laboratory methods. Statistical analyses were conducted to evaluate differences in liver function parameters across the five pandemic waves, with significance set at P < 0.05. Results: The median age of the hospitalized patients (N = 1501) was 61 ± 21.8 years, with the majority being male (816, 54.3%). The Kruskal-Wallis test showed a significant increase in the median levels of ALP, total bilirubin, and direct bilirubin in the first wave; the AST and ALT in the third wave; and serum albumin in the second wave (P < 0.001). The median serum levels of total bilirubin and direct bilirubin were significantly higher in older patients compared to younger patients (P < 0.001), and the median ALT and serum albumin were significantly lower in older patients (P < 0.0001). In males, the median values of AST, ALT, total bilirubin, and direct bilirubin were significantly higher than in females (P < 0.0001). The median values of all parameters, except serum albumin, in deceased patients were significantly higher compared to discharged patients, and serum albumin was significantly lower. Conclusions: In this descriptive study, we observed that older and male patients were more frequently hospitalized than females. Our findings showed variations in liver parameters across different pandemic waves, suggesting distinct behaviors of various SARS-CoV-2 strains.

Lessons from an 11-year retrospective cohort study of Escherichi coli causing UTI in Imam Hospital Ardabil, Iran

Background and Objectives: The global problem of urinary tract infections (UTIs) caused by antibiotic-resistant bacteria is due to limited treatment options. This study aimed to examine the prevalence, etiology, and management implications of Escherichi coli causing UTI at Imam Hospital Ardabil, Iran. Materials and Methods: 2340 samples of retrospective data on E. coli causing UTIs were collected at Imam Hospital in Ardabil, Iran, spanning from 2012 to 2022. The samples were cultured and isolated, and their antibiotic susceptibility was determined using standard laboratory methods and data were then organized and systematically categorized using Python. Results: It was found that the lowest level of resistance was related to nitrofurantoin, followed by imipenem. In 2018, the number of E. coli patients resistant to trimethoprim was the highest. Cephalexin and ciprofloxacin trends indicate the reduc- tion of the line during this retrospective period. There was a significant correlation between wards and some antibiotics like Cefepime, Cefotaxime, Ceftazidime, and Trimethoprim (P-Value <0.05). Conclusion: Significant correlations were identified between specific hospital wards and resistance to antibiotics. These findings underscore the need for continuous surveillance and tailored antibiotic stewardship programs to combat the rising trend of antibiotic resistance.

Antibacterial Activities of Leaf Extracts and Synthesized Silver Nanoparticles from Allium sativum on Urinary Quinolone-resistant Escherichia coli

Aims: The study was aimed at evaluation of the antibacterial activities of crude leaf extracts and synthesized Ag-NPs from Allium sativum on urinary quinolone resistant E. coli. Study Design: Cross sectional study. Place and Duration of Study: Department of Microbiology, Nasarawa State University, Keffi, between November 2023 and October 2024. Methodology: Confirmed Samples for this study were collected from selected General Hospitals in Abuja Municipal, Nigeria. The phytochemical screening of the Allium sativum leaf ethanolic extract (ASE) for various phytochemical constituents and detection of AgNPs was conducted using laboratory method and other methods; UV-visible spectra, and Fourier Transform Infrared Spectroscopy (FTIR). Results: All isolates were resistant to AMP and CIP. All the E. coli isolated were MAR isolates. All the MAR isolates had MAR indices of ≥ 0.2. Most isolates were MDR isolates. There was also a PDR and XDR isolates among the selected tested E coli isolates. Phytochemical screening of aqueous, ethanolic, ethyl acetate and n-hexane leaf extracts of Allium sativum showed presence of only glycosides in all the extracts. Phenols and resins followed after as they were only absent in the aqueous extract of A. sativum leaf while tanins, steroids, saponins and pholabatanins were present in two (2) of the four (4) extract analyzed. Antibacterial activity screening of aqueous, ethanoic, ethyl acetate and n-hexane leaf extracts of Allium sativum were evaluated against quinolone resistant E. coli showed activity by only aqueous and ethanolic extracts. The ethanolic extracts were more active. Synthesized silver nanoparticles of the active extracts have shown higher antibacterial activity against the responsive isolates than their corresponding crude extracts. Conclusion: The synthesized silver nanoparticles from the active leaf extracts exhibited greater antibacterial activity against the responsive isolates compared to their corresponding crude extracts. These findings suggest that AgNPs hold potential for use in medicine to prevent both infectious and non-infectious diseases.

Agreement between clinical criteria and quantitative polymerase chain reaction for diagnosing scabies in Auckland children.

We sought to determine the degree of agreement between clinical and laboratory methods for diagnosing scabies in school-aged children. Clinical information and samples were collected from children aged 7 months to 14 years attending educational institutions in Auckland, New Zealand. Two methods determined scabies status: the International Alliance for the Control of Scabies clinical criteria (IACS) and quantitative polymerase chain reaction (qPCR). Sensitivity and specificity of each method, as the reference or index standard, were estimated and agreement was determined using Cohen's kappa statistic. Sixteen of 145 children were positive based on IACS criteria and 15 of 64 with a suspicious skin lesion returned a positive qPCR test. IACS sensitivity and specificity were 66.7% (95% confidence interval (CI): 39.9-93.3) and 94% (95% CI: 89.9-98.0), respectively (with qPCR as the reference). For qPCR, sensitivity and specificity were 50% (95% CI: 25.5-74.5) and 96.9% (95% CI: 94.0-100.0), respectively (with IACS as the reference). The kappa value was 0.53. Agreement between clinical and laboratory methods in the identification of scabies diagnosis was moderate. Both methods had low sensitivity but high specificity. Scabies diagnosis might be improved, thereby enhancing control measures, by relaxing the IACS criteria (as some IACS-negative participants returned positive qPCR tests, indicating mite DNA was present) and conversely supplementing clinical assessment with qPCR testing.

Application of a Screen-Printed Ion-Selective Electrode Based on Hydrophobic Ti3C2/AuNPs for K+ Determination Across Variable Temperatures.

Monitoring potassium ion (K+) concentration is essential in veterinary medicine, particularly for preventing hypokalemia in dairy cows, which can severely impact their health and productivity. While traditional laboratory methods like atomic absorption spectrometry are accurate, they are also time-consuming and require complex sample preparation. Ion-selective electrodes (ISEs) provide an alternative that is faster and more suitable for field measurements, but their performance is often compromised under variable temperature conditions, leading to inaccuracies. To address this, we developed a novel screen-printed ion-selective electrode (SPE) with hydrophobic Ti3C2 Mxene and gold nanoparticles (AuNPs), integrated with a temperature sensor. This design improves stability and accuracy across fluctuating temperatures by preventing water layer formation and enhancing conductivity. The sensor was validated across temperatures from 5 °C to 45 °C, achieving a linear detection range of 10-⁵ to 10-1 M and a response time of approximately 15 s. It also demonstrated excellent repeatability, selectivity, and stability, making it a robust tool for K+ monitoring in complex environments. This advancement could lead to broader applications in other temperature-sensitive analytical fields.

Inline Measurement of Light Beam Induced Current (LBIC) Under High-Injection and Reverse Bias Conditions

Quality control in solar cell production relies on characterization methods that are fast enough to yield information on the properties of each solar cell in less than about one second. Imaging techniques such as electroluminescence (EL) are well established methods revealing spatially resolved quality mappings. Scanning techniques such as light beam induced current (LBIC) are common laboratory methods yielding complementary information but do not meet the speed requirements. In our work, we analyse an inline implementation of the LBIC method which is extended with respect to its measurement parameters, i.e., both the laser power and a solar cell bias-voltage are varied. As these extended conditions differ from conventional LBIC-applications at zero bias and low injection, we compare our inline-LBIC images with EL images and conventional LBIC images by means of an image contrast analysis. We find that our method resembles more the EL imaging as variations in the local series resistance are prominently detected. Thus, the proposed LBIC approach with extended measurement parameter range can yield both local short circuit information and local series resistance information. With our setup, measurement speeds around 700 ms are achieved.

Update on syphilis diagnostics.

Syphilis is rising globally, with resultant increases in morbidity and mortality that disproportionately impact underserved populations. Appropriate screening and testing for syphilis with accurate, reliable, affordable, and timely assays is crucial for combating this epidemic. This review provides a brief overview of laboratory methods for syphilis diagnosis, with a focus on recent updates in diagnostics and directions for future research. Syphilis can be complex and time-consuming to diagnose and stage appropriately. The historic use of darkfield microscopy for diagnosis has been eclipsed by algorithms that include both nontreponemal and treponemal antibody tests for screening and confirmation of active Treponema pallidum infection. Newer diagnostic modalities include nucleic acid amplification assays (NAATs) and point-of-care testing (POCT), which hold promise for increasing identification of active syphilis but have notable limitations. More work is needed to develop accurate, reliable, affordable, and expeditious tests to optimize syphilis diagnosis. Algorithms utilizing a combination of serological treponemal and nontreponemal assays remain standard of care for the diagnosis of syphilis, but recently developed NAATs and POCT assays present opportunities to increase syphilis detection. Further research is warranted to improve upon these testing modalities and explore other markers that could aid in syphilis diagnosis.

Assessing Asphalt Binder Aging with 1H Spin-lattice NMR Relaxometry: A Comparative Study of Temperature and UV Radiation Effects

Objective: Asphalt binder, a byproduct of the crude-oil refining process, is commonly used in road construction due to its favorable response to physical stresses. However, it is also susceptible to environmental aging, including temperature variations and ultraviolet (UV) radiation. Standard laboratory methods for studying asphalt binder aging primarily focus on factors like temperature, pressure, and oxygen, often neglecting the impact of UV radiation. This study employs 1H spin-lattice nuclear magnetic resonance (NMR) relaxometry to investigate the effects of UV radiation on asphalt binder aging compared to temperature-induced aging. Methods: Primary relaxation times and ratios were derived from a bi-exponential fit of the experimental relaxation decay induced by a 200-MHz NMR magnet. NMR relaxometry analysis revealed that 90% (0.9 primary ratio) of the protons in unaged asphalt binders exhibited a characteristic primary spin-lattice relaxation time (T1) of approximately 470ms. Results: Cold exposure did not significantly alter these parameters. Mimicked heat aging, which considered only temperature and duration, resulted in slight increases in both the primary relaxation time and ratio. In contrast, after 72h of UV exposure, binders showed variable T1 values at a significantly decreased primary ratio. This variability was summarized with the new performance parameter, the Herbaw. Further testing showed that standardized heat aging, which considered sample size and pressure, reduced both the primary relaxation time and ratio when compared to the mimicked aging. Conclusion: These results demonstrate that UV radiation induces significant structural changes in asphalt binder, which can be effectively detected using spin-lattice NMR relaxometry. The Herbaw performance parameter was successful in describing the variability of the UV aging which greatly impacted the primary ratio, indicating oxidative stress. The Herbaw Parameter was not as successful in describing heat aging since only slight changes in the primary relaxation time were detected. While the hydrogen environments were not significantly impacted, temperature-based aging may depend on multiple mechanisms.

Comparison of the BluePoint MoldID oligonucleotide array and Bruker Biotyper MALDI-TOF MS for the identification of filamentous fungi.

The BluePoint MoldID kit is an oligonucleotide array used for the identification of filamentous fungi, and it has not yet been mentioned in recent studies. We used a BluePoint MoldID kit to identify standard and clinical filamentous fungal isolates and compared its performance with that of Bruker MALDI-TOF MS. The former accurately identified 80.2% of the isolates (142/177), and the latter identified 92.6% of the isolates (164/177). The performance of the BluePoint MoldID kit was slightly inferior to that of Bruker MALDI-TOF MS because of the smaller database. However, the BluePoint MoldID kit can cover most clinically common opportunistic fungal infections; thus, it offers an alternative method for laboratories that lack MALDI-TOF MS equipment, as the device is less expensive.

Blockchain Technology and Industry 5.0 synergy for sustainable development in RMG industries: an ISM and fuzzy DEMATEL approach

This research explores the contribution of Blockchain Technology and Industry 5.0 in driving sustainability within Bangladeshi Ready-Made Garments (RMG) industry, with a focus on alignment with key Sustainable Development Goals (SDGs). The study employs Interpretive Structural Modeling (ISM) and fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL) methods to identify and analyze 14 critical synergies that can drive sustainability. The ISM analysis categorizes the synergies into independent, dependent, and linkage variables, providing insights into their roles and significance within the system. Fuzzy DEMATEL further refines this understanding by evaluating the direct and indirect relationships among the linkage synergies. Key findings reveal the importance of synergies such as reverse logistics and recycling, supply chain collaboration & visibility and ethical practices in driving sustainability. This research contributes by offering a detailed analysis of how the synergy between Blockchain technology and Industry 5.0 can enhance sustainability practices in the RMG industry, providing actionable insights into the technological transformation of supply chain dynamics in support of global sustainability targets.

M5C‐TNKmer: Identification of 5‐Methylated Base Cytosine of Ribonucleic Acid Using Supervised Machine Learning Techniques

ABSTRACT5‐Methylcytosine (m5C) is a widely recognized epigenetic modification in ribonucleic acid (RNA), catalyzed by methyltransferases. This modification is crucial for various biological functions. While the role of m5C in deoxyribonucleic acid (DNA) has been extensively studied, its role in RNA is still in its early stages of exploration. Accurate and systematic detection and classification of m5C sites in RNA remain challenging tasks. Machine learning techniques offer an efficient alternative to traditional laboratory methods for identifying m5C sites in Homo sapiens. This study introduces a novel computational model m5C‐TNKmer, which utilizes k‐mer feature extraction to enhance the identification of m5C sites in RNA sequences. Four sub‐datasets derived from the primary dataset Di‐nucleotide (DNC), Tri‐nucleotide (TNC), Tetra‐nucleotide (Tetra‐NC), and Penta‐nucleotide (Penta‐NC) were used to train the model. The results demonstrated that m5C‐TNKmer achieved an impressive accuracy of 96.15%. This model provides a powerful tool for scientists to accurately identify RNA m5C sites, contributing to a deeper understanding of genetic functions and regulatory mechanisms.

A fully automated morphological analysis of yeast mitochondria from wide-field fluorescence images

Mitochondrial morphology is an important parameter of cellular fitness. Although many approaches are available for assessing mitochondrial morphology in mammalian cells, only a few technically demanding and laborious methods are available for yeast cells. A robust, fully automated and user-friendly approach that would allow (1) segmentation of tubular and spherical mitochondria in the yeast Saccharomyces cerevisiae from conventional wide-field fluorescence images and (2) quantitative assessment of mitochondrial morphology is lacking. To address this, we compared Global thresholding segmentation with deep learning MitoSegNet segmentation, which we retrained on yeast cells. The deep learning model outperformed the Global thresholding segmentation. We applied it to segment mitochondria in strain lacking the MMI1/TMA19 gene encoding an ortholog of the human TCTP protein. Next, we performed a quantitative evaluation of segmented mitochondria by analyses available in ImageJ/Fiji and by MitoA analysis available in the MitoSegNet toolbox. By monitoring a wide range of morphological parameters, we described a novel mitochondrial phenotype of the mmi1Δ strain after its exposure to oxidative stress compared to that of the wild-type strain. The retrained deep learning model, all macros applied to run the analyses, as well as the detailed procedure are now available at https://github.com/LMCF-IMG/Morphology_Yeast_Mitochondria.

Evaluation of the dynamics of nutrients and potentially toxic elements along a major river in Ethiopia using multivariate statistical techniques: Implications of possible co-occurrences

This study utilized established field and laboratory methods and multivariate statistical tools to evaluate the nutrient and potentially toxic elements (PTEs) distribution, identify possible sources, and determine potential co-existence in the Awash River. The levels of soluble reactive phosphorus (SRP), total phosphorus (TP), NO3-N, Mn, Ni, Cr, and Cu generally increased downstream in the upper Awash, with the highest respective values of 0.70, 1.34, 1.19, 1.58, 1.03, 0.85, and 0.11 mg L−1 at the inlet to Lake Koka. Sites found downstream of the inflow of Lake Beseka and Metehara town showed the highest levels of Fe, B, Zn, and dissolved silica. Principal components and correlation analysis findings revealed strong associations (r ≥ 0.80, p < 0.05) between nutrient parameters (SRP, TP, and NO3-N) and PTEs (Cu, Ni, Mn, and Cr), implying common origins and potential co-occurrences. The potential co-occurrences of these parameters may strengthen their potential individual impacts due to complex interactions.

Guidelines for the diagnosis and management of multiple myeloma in China (2024 revision)

Multiple myeloma (MM), an incurable clonal plasma cell dysplasia, is the second most common hematological malignancy in many countries, mainly developing in the elderly population. With the emergence of novel agents and laboratory methods, the diagnosis and treatment of MM have been significantly improved. In this version of the "Guidelines for the diagnosis and management of multiple myeloma in China (2024 revision)", several examination items have been updated in the diagnostic section; the definition of ultra high-risk MM has been proposed in the risk stratification section; for patients with equal or more than second-line relapse, chimeric antigen receptor T cell therapy and a bispecific T-cell engager have been added; and the treatment recommendations have been listed at different levels based on the best available evidence.

Resolving contradictions in green supply chain management: A combined TRIZ and DEMATEL approach

Companies are increasingly required to adopt green supply chain practices to enhance their ecological footprint and financial viability, driven by global environmental concerns. This research focuses on resolving the contradictions faced in green supply chain management (GSCM) implementation through a combined application of the Theory of Inventive Problem Solving (TRIZ) and the Decision-Making Trial and Evaluation Laboratory (DEMATEL) methods. Five key contradictions were identified: regulatory enhancements vs. resource limitations, technological unreadiness vs. regulatory refinement, profitability vs. customer trust, collaboration vs. competitiveness, and green material prioritization vs. scarcity. The study proposes 18 inventive principles to address these contradictions, including strategies such as flexible technology adoption and market segmentation. DEMATEL is then applied to analyze the interactions between these principles, offering a structured model for strategic decision-making. The DEMATEL analysis revealed that government support plays the most critical role in driving green supply chain adoption, influencing other strategies significantly. This integrated approach provides practical guidance for stakeholders, helping to shape policies and improve GSCM implementation in industries, particularly within the packaging and paper products sector in Indonesia.

Comparative evaluation of laboratory methods for performance assessment of cementitious materials in wastewater networks: Biological and chemical tests versus field exposure

The biodeterioration of concrete elements in sewer systems and their repair is of significant economic and societal concern. However, the available test methods to assess the performance of cementitious materials under the relevant conditions are insufficiently validated. In the present study, two biological test methods and a standardised chemical test were applied to two sewer repair mortars and a reference mortar, and the performances of these materials were compared in a severely deteriorating sewer environment. In both biological tests, the induction period was considerably shorter than that of the field, and time-resolved recording of durability indicators enabled to determine deterioration rates in the steady-state regime, which compared reasonably well with each other and with the behaviour in the sewer environment. The chemical test does not allow to obtain a deterioration rate, and the observed relative performance differences of the mortars deviated from the results of the biological tests.

EDXRF and Machine Learning for Predicting Soil Fertility Attributes

Soil fertility evaluation is fundamental for sustainable agricultural practices, often relying on conventional laboratory methods. These methods, while accurate, are labor-intensive, time-consuming, and require chemical reagents. Spectroscopic sensors, such as energy-dispersive X-ray fluorescence (EDXRF), offer a rapid and non-destructive alternative but require calibration of machine learning models for accurate prediction of fertility attributes. In this context, this study compares the performance of four machine learning algorithms—multiple linear regression (MLR), partial least square regression (PLS), support vector machine regression (SVM), and random forest regression (RF)—in predicting soil pH, organic carbon (SOC), sum of exchangeable bases (BS), and cation exchange capacity (CEC) using EDXRF data from two soil datasets. Results indicate that PLS models outperformed others (the hierarchy of accuracy was PLS &gt; MLR &gt; SVM &gt; RF). Overall, we emphasize the benefits of integrating PLS with EDXRF, capable of mitigating the use of traditional soil analysis.

Case Report: Soft tissue infection with Burkholderia thailandensis capsular variant: case report from the Lao PDR

Background Burkholderia thailandensis is an environmental bacteria closely related to Burkholderia pseudomallei that rarely causes infection in humans. Some environmental isolates have shown to express a capsular polysaccharide known as B. thailandensis capsular variant (BTCV), but human infection has not previously been reported. Although B. thailandenisis has been identified in environmental samples in Laos before, there have not been any human cases reported. Case A 44-year-old man presented to a district hospital in Laos with a short history of fever and pain in his left foot. Physical examination identified a deep soft-tissue abscess in his left foot and an elevated white blood count. A deep pus sample was taken and melioidosis was suspected from preliminary laboratory tests. The patient was initially started on cloxacillin, ceftriaxone and metronidazole, and was then changed to ceftazidime treatment following local melioidosis treatment guidelines. Laboratory methods A deep pus sample was sent to Mahosot Hospital microbiology laboratory where a mixed infection was identified including Burkholderia sp. Conventional identification tests and API 20NE were inconclusive, and the B. pseudomallei-specific latex agglutination was positive. The isolate then underwent a Burkholderia species specific PCR which identified the isolate as B. thailandensis. The isolate was sent for sequencing on the Illumina NovaSeq 6000 system and multi-locus sequence typing analysis identified the isolate had the same sequence type (ST696) as B. thailandensis E555, a strain which expresses a B. pseudomallei-like capsular polysaccharide. Conclusion This is the first report of human infection with B. thailandensis in Laos, and the first report of any human infection with the B. thailandensis capsular variant. Due to the potential for laboratory tests to incorrectly identify this bacteria, staff in endemic areas for B. thailandensis and B. pseudomallei should be aware and ensure that appropriate confirmatory methods are used to differentiate between the species.

Molecular Dynamics Simulations Elucidate the Molecular Organization of Poly(beta-amino ester) Based Polyplexes for siRNA Delivery.

Cationic polymers are known to efficiently deliver nucleic acids to target cells by encapsulating the cargo into nanoparticles. However, the molecular organization of these nanoparticles is often not fully explored. Yet, this information is crucial to understand complex particle systems and the role influencing factors play at later stages of drug development. Coarse-grained molecular dynamics (CG-MD) enables modeling of systems that are the size of real nanoparticles, providing meaningful insights into molecular interactions between polymers and nucleic acids. Herein, the particle assembly of variations of an amphiphilic poly(beta-amino ester) (PBAE) with siRNA was simulated to investigate the influence of factors such as polymer lipophilicity and buffer conditions on the nanoparticle structure. Simulations were validated by wet lab methods including nuclear magnetic resonance (NMR) and align well with experimental findings. Therefore, this work emphasizes that CG-MD simulations can provide underlying explanations of experimentally observed nanoparticle properties by visualizing the nanoscale structure of polyplexes.