Advanced Laboratory Research Articles

Development of a Comprehensive Pollen and Spore Catalog Using Advanced Laboratory Techniques: A Case Study of Contemporary Dried and Fresh Flower Specimens from Bangladesh

This study focuses on the preparation of dry and fresh flower samples for pollen and spore observation using advanced laboratory techniques, identification of morphological characteristics, and the development of a pollen catalog that provides valuable insights into ecology and pollen morphology for different taxa. This research contributes to the field of palynology, an essential discipline in stratigraphy and biostratigraphy, by creating a detailed pollen catalog that enhances our understanding of paleoenvironmental conditions, depositional history, and potential hydrocarbon presence. Twenty-six fresh and dried flower samples from Chattogram, Cox’s Bazar, and Dhaka Districts have been analyzed using acetolysis techniques. Pollen morphologies were examined at 400x and 1000x magnifications through transmitted and fluorescence light microscopy, and high-resolution imaging of one species was further enhanced with Field Emission Scanning Electron Microscopy (FESEM). Pollen morphology documented for twenty-five species across twelve families, including Fabaceae, Asteraceae, Lamiaceae, Solanaceae, Poaceae, Rubiaceae, Campanulaceae, Melastomataceae, Malvaceae, Verbenaceae, Oleaceae, and Heliotropiaceae as well as one spore from the Lygodiaceae family. The resulting catalog provides valuable ecological insights by highlighting morphological features and taxonomic classifications. It is an essential resource for researchers and professionals involved in Holocene pollen studies. This work contributes to the understanding of palynology and underscores the importance of advanced analytical technologies in reconstructing the prehistoric environment of Bangladesh. The data gathered is crucial for comprehending the ecological evolution of the world's largest delta.

Diagnosis and treatment of infection specific to the perinatal period (Draft clinical recommendations for discussion by neonatologists and pediatricians)

Perinatal infections occupy a leading place among the causes of neonatal morbidity, maternal and perinatal mortality. Infections are among the main causes of termination of pregnancy and premature birth. The practical recommendations presented in the work are intended for doctors of obstetric institutions in order to make a clinical diagnosis of an infection specific to the perinatal period, the tactics of examination and treatment of newborn children. The clinical recommendations correspond to the latest scientific data on the topic, contain information that is applied to the practical activities of a neonatologist, intensive care specialist and pediatrician. These clinical recommendations contain information about infections specific to the perinatal period, including the definition, frequency of occurrence, etiology of infections, pathogenetic mechanisms of disease development Numerous high-risk factors for infection of the fetus and newborn are described in detail. The document discusses and proposes the classification of the disease, the criteria for the adoption of the diagnosis. The features of the clinical picture of the disease are described, it is noted that the inflammatory process in a newborn child can be localized in any organ or acquire a systemic (generalized) character, in some cases, the ingress of an infectious agent into a macroorganism is not necessarily accompanied by clinical manifestations, which indicates an asymptomatic or subclinical course of infection. The recommendations provide advanced laboratory and instrumental diagnostics. The stages of treatment are described, including the choice and correction of antibacterial therapy, taking into account the peculiarities of the mother’s anamnesis, the child’s gestation period and the etiology of the disease. These clinical recommendations have been prepared taking into account the level of credibility of the recommendations and the level of reliability of the evidence.These practical recommendations are offered for public discussion and are posted in full on the website of the Ministry of Health of the Russian Federation.

A correlation for cyclic degradation of natural clayey and sandy soils at different strain amplitudes

Cyclic degradation of soil significantly affects its behavior in seismic analyses, especially at relatively large strain levels. Beyond the threshold shear strain for degradation, soil properties, including its stiffness and damping, may change dramatically with each loading cycle. The present study aims to extend the investigation by probing the effect of cyclic degradation in greater detail, interpreting results from cyclic tests conducted at an advanced laboratory. In this regard, the results of 77 cyclic tests on natural sandy and clayey soils were analyzed. It was observed that the threshold strain for degradation is 1–2 × 10−4 for clayey soils and 3 to 4 × 10−4 for sandy soils. Furthermore, a correlation is proposed between degradation parameters and strain, which is useful for predicting the shear modulus for a desired loop number in cases where only the shear modulus of the 1st loop is available. To ensure the accuracy of this correlation, two additional tests were conducted in the laboratory. The predictions showed satisfactory agreement with the measurements. It was observed that after 15 loading cycles, the shear modulus of the soil decreased to 30–40 % of its initial value at the first cycle. This degraded modulus could be estimated using the correlation proposed in this study, with a 10 % margin of error. This validation supports the applicability of the proposed correlation.

Insights into the Sex-Related Effects of Dietary Polyphenols and Metabolic Disruptors on Inflammatory and (Neuro) Endocrine Pathways in Obesity: The HEAL Project.

this study was performed under the umbrella of the Health Extended Alliance for Innovative Therapies, Advanced Lab Research, and Integrated Approaches of Precision Medicine (HEAL ITALIA) partnership and funded under the National Recovery and Resilience Plan, Mission 4 Component 2 Investment 1.3, and by the European Union. the overall objective of the HEAL project is to identify innovative and effective therapeutic approaches to reduce disease burden. The present research falls within Spoke 7: Prevention Strategies: Integrated and gender medicine approaches for prevention strategies based on environmental, lifestyle, and clinical biometric data. Obesity represents a primary risk factor worldwide for the onset of numerous life-threatening diseases, including metabolic, cardiovascular, and neurological diseases. Environmental and gender-related factors influence obesity development. However, the molecular mechanisms underlying the effects of those agents on different organs of the human body are not fully understood yet. here, we present a study protocol aimed at shedding light on (i) the complex interplays among adipose tissue, brain and gut in obesity, and (ii) the effects of specific dietary components and environmental metabolism-disrupting compounds on those interactions. To this purpose, we combined ex vivo, in vitro, and in vivo approaches to gain additional knowledge about the molecular mechanisms underlying connections between organs. the data provided by this study will contribute to defining new targets for therapeutic and/or preventive interventions, thereby allowing more personalized approaches to nutrition.

Whole genome analysis of Pantoea species identified from sepsis patients in selected Ethiopian referral hospitals: emerging pathogens

BackgroundThe burden of sepsis worsens due to the continuation of emerging pathogens such as multidrug-resistant Pantoea species.MethodsA multicenter study was conducted between October 2019 and September 2020 at four hospitals located in central, southern, and northern parts of Ethiopia. A total of 1416 sepsis patients were recruited and blood cultures were performed. At each study site, positive cultures were characterized by their colony characteristics, gram stain, and conventional biochemical tests. All Pantoea species were identified using Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry (MALDI TOF) and subjected to whole genome sequencing (WGS) using Illumina HiSeq 2500. The phylogeny structure of Pantoea isolates was calculated using IQ-TREE v1.6.12 from single-nucleotide polymorphisms detected by Snippy v.4.6.0 and filtered by Gubbins v.2.3.4. Average nucleotide identity was estimated by using OrthoANI v.0.93.1 on Shovill v.1.1.0 assemblies. Antimicrobial resistance genes and plasmid replicons were detected using ARIBA v.2.14.6. Phylogenetic trees were visualized using iTOLv.6.5.2.ResultsMultiple Pantoea species include: P. dispersa (n = 19), P. septica (n = 1), and a novel Pantoea spp. (n = 1), were identified among sepsis patients. All P. dispersa isolates and the novel Pantoea species were isolated at Dessie Referral Hospital and displayed phylogenetic clonality, including the ubiquity of an IncM1 plasmid and identical antimicrobial resistance (AMR) gene profiles, encoding blaCTX−M−15, blaTEM−1D, blaSCO−1, and aac(3)-lla. The novel Pantoea spp. isolate harboured blaCTX−M−9 and blaTEM−1D and carried an IncN3 plasmid replicon. The P. septica was isolated at Tikur Anbessa Specialized Hospital in Addis Ababa and carried no detectable acquired AMR genes.ConclusionThe emerging Pantoea spp. carrying multiple AMR genes were identified from sepsis patients. Implementation of strong infection prevention strategies and building surveillance capacity with advanced bacteriology laboratories capable of identifying multidrug-resistant emerging pathogens is strongly recommended.

AIDM-CT: software for cone-beam X-ray tomography and deep-learning-based analysis

ABSTRACT Non-destructive testing (NDT) with high-resolution cone-beam X-ray computed tomography (XCT) plays a crucial role in revealing the 3D distribution and morphology of defects within an object. It’s necessary to generalise an intelligent and customised XCT-based NDT protocol, providing solutions for reconstruction quality improvement and complex defect quantitative analysis for users. We analysed the key techniques of XCT and developed the systematic software for data acquisition, reconstruction, intelligent super-resolution and segmentation in our advanced imaging and data mining laboratory (AIDM-CT). The experimental results demonstrated the software efficiently achieves the control of XCT scanning, artefact correction algorithms related to cone-beam geometrics, beam hardening, ring and radial artefacts, deep-learning based slice super-resolution and feature segmentation, and quantitative analysis. The software is programmed by Python language to provide the friendly multi-function graphical user interface (GUI), in which the programming of reconstruction and corrections combined with Computer Unified Device Architecture (CUDA) acceleration to guarantee the high efficiency of XCT task. Particularly, the multi-functional super resolution module (MF-GAN) is proposed to optimise the quality of CT image and the improved U-Net segmentation module (CBAM U-Net) is also developed to fulfill the high-precision quantitative non-destructive testing of homogeneous and variform microdefects in our AIDM-CT software.

Is Clinical Medicine Dying?

Recently, I came across a few discussions and write-ups on the dying art of clinical medicine caused by rapid advances in technology, which is replacing previously indispensable instruments such as stethoscope. Fred has interestingly termed it "Hyposkillia."1 Multiple editorials have decried the loss of clinical skills, and medical educators justify not only teaching but also using basic history-taking and physical examination skills in routine patient care.2-4 However, some skeptics suggest that emphasis on clinical skills is from a bygone era and that the availability of advanced imaging techniques and laboratory tests has supplanted ambiguous history and physical findings.5,6 Here is what I think.

Effectiveness of Communication Board on Level of Satisfaction among Mechanically Ventilated Patients at Intensive Care Unit in a Tertiary Hospital

Introduction: Critical care nurses are crucial in managing critical patients, facing challenges with advanced technology, alarms, ventilators, and multiple laboratory investigations. They must effectively communicate and manage patients on mechanical ventilation (MV), a lifesaving intervention for those needing oxygenation and ventilation support to ensure patient satisfaction. Materials and Methods: The study employed a quasi-experimental design with 80 mechanically ventilated patients selected through purposive sampling. Data were collected using demographic and clinical pro forma and a predesigned four-point Likert satisfaction scale comprised 14 items. The intervention group utilized a communication board, while the conventional group received routine care. The aim was to evaluate satisfaction levels in both groups, followed by a posttest on the 5th day using the same instrument. Results: The pretest revealed mean satisfaction scores of 32.47 ± 6.48 and 33.95 ± 6.41 for the intervention and conventional groups, respectively, with a mean difference of 1.47, considered statistically nonsignificant (t 78 = 1.023, P = 0.310). Conversely, posttest scores showed 37.85 ± 8.23 and 34.32 ± 6.18 for the intervention and conventional groups, respectively, with a mean difference of 3.53, indicating statistical significance (t 78 = 2.164, P = 0.034). Hence, the communication board intervention significantly enhanced satisfaction scores among mechanically ventilated patients, underscoring its positive impact on nursing care in terms of patients’ satisfaction. Conclusion: Effective communication is crucial in intensive care unit patient care, especially for those unable to speak due to MV. Utilizing communication boards significantly enhances patient satisfaction, highlighting the need for ongoing innovation in critical care nursing.

Enhancing quantitative imaging to study DNA damage response: A guide to automated liquid handling and imaging

Laboratory automation and quantitative high-content imaging are pivotal in advancing diverse scientific fields. These innovative techniques alleviate the burden of manual labour, facilitating large-scale experiments characterized by exceptional reproducibility. Nonetheless, the seamless integration of such systems continues to pose a constant challenge in many laboratories. Here, we present a meticulously designed workflow that automates the immunofluorescence staining process, coupled with quantitative high-content imaging to study DNA damage signalling as an example. This is achieved by using an automatic liquid handling system for sample preparation. Additionally, we also offer practical recommendations aimed at ensuring the reproducibility and scalability of experimental outcomes. We illustrate the high level of efficiency and reproducibility achieved through the implementation of the liquid handling system but also addresses the associated challenges. Furthermore, we extend the discussion into critical aspects such as microscope selection, optimal objective choices, and considerations for high-content image acquisition. Our study streamlines the image analysis process, offering valuable recommendations for efficient computing resources and the integration of cutting-edge deep learning techniques. Emphasizing the paramount importance of robust data management systems aligned with the FAIR data principles, we provide practical insights into suitable storage options and effective data visualization techniques. Together, our work serves as a comprehensive guide for life science laboratories seeking to elevate their high-content quantitative imaging capabilities through the seamless integration of advanced laboratory automation.

Understanding the dynamics of nipah virus (NiV) transmission and outbreaks in India from Kerala’s perspective

This comprehensive analysis delves into the series of Nipah virus (NiV) outbreaks across India, with a particular focus on occurrences in Kerala. NiV, which belongs to the Paromyxoviridae family and Henipavirus genus, originated in Malaysia in 1998 and has consistently posed significant global health threats. In India, NiV outbreaks have sporadically emerged since the initial case in West Bengal in 2001, often with alarming mortality rates. The 2018 resurgence in Kerala exhibited an astonishing case fatality rate of 89%, emphasizing the need for tailored diagnostic and management strategies due to substantial variability in the incubation period and clinical manifestations. Understanding the predominant person-to-person transmission underscores the importance of comprehending transmission dynamics. Early detection, facilitated by the Integrated Disease Surveillance Program (IDSP), remains vital, as treatment options are currently confined to supportive care, necessitating the exploration of more effective therapeutics. The sporadic nature of NiV outbreaks, exemplified by the recent Kerala episode, emphasizes the urgency for robust response mechanisms, while collaborative efforts and capacity-building initiatives are essential for effectively managing these occurrences. Continued focus on prompt detection, advanced laboratory testing, accessibility to cutting-edge facilities, and heightened infection control measures remains imperative to mitigate future incidents.

Experimental investigation of enhanced CO2 refrigeration systems at varying operating condi-tions

The efficiency of a CO2 refrigeration system depends mainly on the operating conditions and the system design. To increase the energy efficiency, advanced system designs include additional components and their combinations such as parallel compression, ejectors, and expansion machines. For a direct comparison of different system designs, measurements were performed on an advanced CO2 laboratory refrigeration system at different operating conditions. The system behaviour was investigated at different gas cooler outlet temperatures, varying cooling loads, different evaporation temperatures and amounts of superheating. The results of the measurements performed on a baseline system configuration and advanced system designs are presented. It was observed that the influence of operating conditions is less important for certain measures in terms of efficiency improvement than for others. For each system design, operating conditions were identified under which a particularly advantageous behaviour of the respective measures was found. In the future, this will allow the judgment of the efficiency enhancement of each of different respective features for each individual application.

Pemasaran dan Peningkatan Kualitas Produk Intellimice Classifier dengan Implementasi Strategi STP (Segementasi, Targeting, Positioning)

The STAS-RG laboratory recently launched the Intellimice Classifier product, a groundbreaking innovation in biomedical and pharmaceutical research that offers advanced laboratory mouse classification technology to enhance research efficiency and accuracy. Although this product promises great potential, STAS-RG faces challenges in identifying the right market for this product. This study aims to identify optimal market opportunities by applying the STP (Segmenting, Targeting, Positioning) strategy and using qualitative methods, including in-depth interviews and field observations. The study results show that the most effective market segmentation includes healthcare institutions, particularly pharmaceutical companies, focusing on individuals aged 20-50, including students and professionals in related fields. The primary target market is pharmaceutical institutions that require efficient and accurate laboratory mouse classification tools to support their research. Intellimice Classifier is positioned as an advanced solution with competitive pricing, utilizing Sensor Computer Vision technology to meet various specific needs in genetic research, such as classifying the gender, weight, color, and size of mice. This study emphasizes the importance of a deep understanding of the market to design effective marketing strategies and tailor the product to customer needs. These findings provide valuable strategic insights for STAS-RG to formulate a more targeted and adaptive marketing approach, aiming to maximize the product's adoption and success in the ever-evolving market. This approach not only allows STAS-RG to effectively introduce the product but also to meet the specific needs of their target market.

Probing coherent phonons in the advanced undergraduate laboratory

Probing coherent phonons in the advanced undergraduate laboratory

N-Alkanes formed by methyl-methylene addition as a source of meteoritic aliphatics

Aliphatics prevail in asteroids, comets, meteorites and other bodies in our solar system. They are also found in the interstellar and circumstellar media both in gas-phase and in dust grains. Among aliphatics, linear alkanes (n-CnH2n+2) are known to survive in carbonaceous chondrites in hundreds to thousands of parts per billion, encompassing sequences from CH4 to n-C31H64. Despite being systematically detected, the mechanism responsible for their formation in meteorites has yet to be identified. Based on advanced laboratory astrochemistry simulations, we propose a gas-phase synthesis mechanism for n-alkanes starting from carbon and hydrogen under conditions of temperature and pressure that mimic those found in carbon-rich circumstellar envelopes. We characterize the analogs generated in a customized sputter gas aggregation source using a combination of atomically precise scanning tunneling microscopy, non-contact atomic force microscopy and ex-situ gas chromatography-mass spectrometry. Within the formed carbon nanostructures, we identify the presence of n-alkanes with sizes ranging from n-C8H18 to n-C32H66. Ab-initio calculations of formation free energies, kinetic barriers, and kinetic chemical network modelling lead us to propose a gas-phase growth mechanism for the formation of large n-alkanes based on methyl-methylene addition (MMA). In this process, methylene serves as both a reagent and a catalyst for carbon chain growth. Our study provides evidence of an aliphatic gas-phase synthesis mechanism around evolved stars and provides a potential explanation for its presence in interstellar dust and meteorites.

Оценка некоторых закономерностей процессов перекисного окисления липидов при увеитах у детей

Original article Assessment of some patterns of lipid peroxidation processes in uveitis in children O.S. Komarov, M.R. Guseva, S.A. Obrubov, N.M. Galkina Pirogov Russian National Research Medical University, Moscow, Russian Federation Uveitis is characterized by a variety of clinical forms, chronic and recurrent course, severe outcomes, and not always effective therapy. In addition, etiological diagnosis and treatment of patients require more subtle and advanced laboratory methods and deciphering the incompletely studied mechanisms of the pathogenesis of the disease. The work, based on significant clinical material, shows that the activation of polymorphonuclear leukocytes (PMN) in the blood is one of the main reasons for the increased processes of lipid peroxidation (LPO) in uveitis. The activity levels of PMN and LPO clearly correlate and reflect the degree of depth and dynamics of the inflammatory process in uveitis. These indicators more subtly characterize the course of the disease and the dynamics of recovery compared to traditional generally accepted criteria for assessing inflammation. Simultaneous study of the intensity of PMN and LPO on the one hand and assessment of the antioxidant activity (AOA) of the system makes it possible to predict the course of the disease, prescribe adequate therapy and judge the severity and completeness of the process. It has been proven that one of the main blood antioxidant proteins, ceruloplasmin, changes parallel to the clinical picture of uveitis, which can be used as a basis for prescribing antioxidant therapy or for assessing the effectiveness of treatment. Key words: uveitis, lipid peroxidation, antioxidants, ceruloplasmin, polymorphonuclear leukocytes

Advancing common bean (Phaseolus vulgaris L.) disease detection with YOLO driven deep learning to enhance agricultural AI

Common beans (CB), a vital source for high protein content, plays a crucial role in ensuring both nutrition and economic stability in diverse communities, particularly in Africa and Latin America. However, CB cultivation poses a significant threat to diseases that can drastically reduce yield and quality. Detecting these diseases solely based on visual symptoms is challenging, due to the variability across different pathogens and similar symptoms caused by distinct pathogens, further complicating the detection process. Traditional methods relying solely on farmers’ ability to detect diseases is inadequate, and while engaging expert pathologists and advanced laboratories is necessary, it can also be resource intensive. To address this challenge, we present a AI-driven system for rapid and cost-effective CB disease detection, leveraging state-of-the-art deep learning and object detection technologies. We utilized an extensive image dataset collected from disease hotspots in Africa and Colombia, focusing on five major diseases: Angular Leaf Spot (ALS), Common Bacterial Blight (CBB), Common Bean Mosaic Virus (CBMV), Bean Rust, and Anthracnose, covering both leaf and pod samples in real-field settings. However, pod images are only available for Angular Leaf Spot disease. The study employed data augmentation techniques and annotation at both whole and micro levels for comprehensive analysis. To train the model, we utilized three advanced YOLO architectures: YOLOv7, YOLOv8, and YOLO-NAS. Particularly for whole leaf annotations, the YOLO-NAS model achieves the highest mAP value of up to 97.9% and a recall of 98.8%, indicating superior detection accuracy. In contrast, for whole pod disease detection, YOLOv7 and YOLOv8 outperformed YOLO-NAS, with mAP values exceeding 95% and 93% recall. However, micro annotation consistently yields lower performance than whole annotation across all disease classes and plant parts, as examined by all YOLO models, highlighting an unexpected discrepancy in detection accuracy. Furthermore, we successfully deployed YOLO-NAS annotation models into an Android app, validating their effectiveness on unseen data from disease hotspots with high classification accuracy (90%). This accomplishment showcases the integration of deep learning into our production pipeline, a process known as DLOps. This innovative approach significantly reduces diagnosis time, enabling farmers to take prompt management interventions. The potential benefits extend beyond rapid diagnosis serving as an early warning system to enhance common bean productivity and quality.

Neurological manifestations of Flaviviridae, Togaviridae, and Peribunyaviridae as vector-borne viruses.

Vector-borne viruses pose a significant health problem worldwide, as they are transmitted to humans through the bite of infected arthropods such as mosquitoes and ticks. In recent years, emerging and re-emerging vector-borne diseases have gained attention as they can cause a wide spectrum of neurological manifestations. The neurological manifestations of vector-borne viruses encompass a board spectrum of clinical manifestations, ranging from mild and self-limiting symptoms to severe and life-threatening conditions. Common neurological complications include viral encephalitis, acute flaccid paralysis, aseptic meningitis, and various neuromuscular disorders. The specific viruses responsible for these neurological sequelae vary by geographic region and include Orthoflavivirus nilense, Zika virus, dengue virus, chikungunya virus, Japanese encephalitis virus, and tick-borne encephalitis virus. This review focuses on the pathogenesis of these neurologic complications and highlights the mechanisms by which vector-borne viruses invade the central nervous system and trigger neuroinflammatory responses. Diagnostic challenges and strategies for early detection of neurological manifestations are discussed, emphasising the importance of clinical suspicion and advanced laboratory testing.

Evaluation and comparison of biomarkers in decompensated heart failure in a tertiary care center

Objective. This research delves into decompensated heart failure (DHF), aiming to comprehensively evaluate and compare biomarkers within a tertiary care center. Recognizing DHF's clinical challenges and high morbidity and mortality rates, the study seeks to enhance understanding and shed light on underlying mechanisms, particularly the role of biomarkers. Methodology. Utilizing a retrospective cohort design, the study spans electronic health records from 2010 to 2022. Ethical considerations, including IRB approval and informed consent, are paramount. Biomarkers such as cardiac troponins, B-type natriuretic peptide (BNP), and C-reactive protein (CRP) undergo rigorous assessment via advanced laboratory techniques. Statistical analyses, encompassing t-tests and ANOVA, provide a robust foundation for discerning patterns and correlations. This study includes 200 patients diagnosed with DHF (experimental group) and 200 control patients without DHF (control group). Results. Baseline characteristics highlight subtle differences between DHF patients (experimental group) and controls. Biomarker analysis reveals statistically significant elevations in cardiac troponins, BNP, and CRP in DHF cases compared to controls. The mean levels in survivors and non-survivors underscore the potential prognostic value of these biomarkers. ANOVA results suggest no significant differences in age, gender distribution, and BMI between the groups, reinforcing the robustness of the findings. Conclusion. This study significantly contributes to DHF management insights, emphasizing the diagnostic and prognostic potential of biomarkers. The observed disparities in biomarker levels, coupled with consistent baseline characteristics, provide valuable insights for clinical considerations and future research in DHF management. The nuanced interpretation of results not only expands knowledge of DHF but also offers actionable insights for clinicians dealing with this complex condition. The study's comprehensive approach, combining clinical, demographic, and biomarker data, lays a strong foundation for future investigations and interventions in DHF.

Application of fusion property calculations for Kazakhstani oil samples

This study thoroughly investigates the melting properties and solid-state transition temperatures of crude oil from Kazakhstan's oil field, which is critical for predicting wax precipitation. Utilizing advanced laboratory equipment such as gas chromatographs, differential scanning calorimeters (DSC), and pour point testers, we obtained comprehensive data on these parameters. Based on the results, we developed new correlations for the melting point and solid-state transition temperature of crude oil, which demonstrate closer alignment with the reference values for various hydrocarbons' melting points compared to standard prediction models. These findings provide more accurate models for wax deposition, essential for efficient crude oil transportation and processing. The results indicated that implementing these new correlations could lead to significant cost savings by reducing pipeline blockages and maintenance requirements, thereby improving overall operational efficiency.

A Portable Automated Microfluidic Platform for Point-of-Care Testing for Multiple Mycotoxins in Wine.

Food safety requires point-of-care testing (POCT) for mycotoxins, since their presence in wine significantly impacts the wine industry and poses a severe threat to human life. Traditional detection methods are usually limited to detecting one mycotoxin and cannot achieve high-throughput, automated, and rapid quantitative analysis of multiple mycotoxins in real samples. Here, we propose a portable automated microfluidic platform (PAMP) integrating a chemiluminescence (CL) imaging system and a microfluidic chip to realize POCT for multiple mycotoxins in real samples, simplifying complex manual operations, shortening the detection time, and improving the detection sensitivity. Specially, silicone films were used as substrates on microfluidic chips to incubate mycotoxin conjugations, and the streptavidin-biotin (SA-B) system and an indirect immunoassay were implemented on silicone films to improve the sensitivity of reaction results. Interestingly, these methods significantly improved detection results, resulting in sensitive detection of mycotoxins, including zearalenone (ZEA) ranging from 1 to 32 ng/mL, aflatoxin B1 (AFB1) ranging from 0.2 to 6.4 ng/mL, and ochratoxin A (OTA) ranging from 2 to 64 ng/mL. The recovery of samples reached 91.39-109.14%, which verified the reliability and practicability of the PAMP. This PAMP enables sensitive and rapid detection of multiple mycotoxins in markets or wineries that lack advanced laboratory facilities. Therefore, it is essential to develop a portable microfluidic platform for POCT to detect mycotoxins in real samples.