Extraction Methodology Research Articles

A novel machine learning methodology for the systematic extraction of chronic kidney disease comorbidities from abstracts

BackgroundChronic Kidney Disease (CKD) is a global health concern and is frequently underdiagnosed due to its subtle initial symptoms, contributing to increasing morbidity and mortality. A comprehensive understanding of CKD comorbidities could lead to the identification of risk-groups, more effective treatment and improved patient outcomes. Our research presents a two-fold objective: developing an effective machine learning (ML) workflow for text classification and entity relation extraction and assembling a broad list of diseases influencing CKD development and progression.MethodsWe analysed 39,680 abstracts with CKD in the title from the Embase library. Abstracts about a disease affecting CKD development and/or progression were selected by multiple ML classifiers trained on a human-labelled sample. The best classifier was further trained with active learning. Disease names in question were extracted from the selected abstracts using a novel entity relation extraction methodology. The resulting disease list and their corresponding abstracts were manually checked and a final disease list was created.FindingsThe SVM model gave the best results and was chosen for further training with active learning. This optimised ML workflow enabled us to discern 68 comorbidities across 15 ICD-10 disease groups contributing to CKD progression or development. The reading of the ML-selected abstracts showed that some diseases have direct causal effect on CKD, while others, like schizophrenia, has indirect causal effect on CKD.InterpretationThese findings have the potential to guide future CKD investigations, by facilitating the inclusion of a broader array of comorbidities in CKD prognostic models. Ultimately, our study enhances understanding of prognostic comorbidities and supports clinical practice by enabling improved patient monitoring, preventive strategies, and early detection for individuals at higher CKD development or progression risk.

Federated Learning for IoMT-Enhanced Human Activity Recognition with Hybrid LSTM-GRU Networks

The proliferation of wearable sensors and mobile devices has fueled advancements in human activity recognition (HAR), with growing importance placed on both accuracy and privacy preservation. In this paper, the author proposes a federated learning framework for HAR, leveraging a hybrid Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) model to enhance feature extraction and classification in decentralized environments. Utilizing three public datasets—UCI-HAR, HARTH, and HAR7+—which contain diverse sensor data collected from free-living activities, the proposed system is designed to address the inherent privacy risks associated with centralized data processing by deploying Federated Averaging for local model training. To optimize recognition accuracy, the author introduces a dual-feature extraction mechanism, combining convolutional blocks for capturing local patterns and a hybrid LSTM-GRU structure to detect complex temporal dependencies. Furthermore, the author integrates an attention mechanism to focus on significant global relationships within the data. The proposed system is evaluated on the three public datasets—UCI-HAR, HARTH, and HAR7+—achieving superior performance compared to recent works in terms of F1-score and recognition accuracy. The results demonstrate that the proposed approach not only provides high classification accuracy but also ensures privacy preservation, making it a scalable and reliable solution for real-world HAR applications in decentralized and privacy-conscious environments. This work showcases the potential of federated learning in transforming human activity recognition, combining advanced feature extraction methodologies and privacy-respecting frameworks to deliver robust, real-time activity classification.

Comparative analysis of global urban land surface phenology between the MODIS and VIIRS products and extraction methods.

The reliability of land surface phenology (LSP) derived from satellite remote sensing is crucial for obtaining accurate estimates of the phenological response of vegetation to future climate change in urban ecosystems. Differences in phenological definition and extraction methodology using remote sensing can generate systemic errors in estimating the phenological temperature sensitivity to predict the biological response of vegetation. Here, we evaluated the start of the season (SOS), the end of the season (EOS), and the growing season length (GSL) between the Terra and Aqua combined Moderate Resolution Imaging Spectroradiometer (MODIS) Land Cover Dynamics (MCD12Q2) and the Suomi National Polar-Orbiting Partnership NASA Visible Infrared Imaging Radiometer Suite (VIIRS) Land Cover Dynamics (VNP22Q2) over 1470 urban clusters worldwide. We found that the availability of valid phenological estimation in urban areas was low across climates, and cities without valid phenological data were mainly distributed in tropical and dry climate zones. The phenological comparison for each urban cluster worldwide revealed significant differences between the two products. For SOS, EOS, and GSL, only a small proportion of urban clusters (6.01%, 3.54%, and 1.50%, respectively) exhibited R2 surpassing 0.5, and approximately 31.63%, 37.37%, and 58.57% showed the RMSD values exceeding two weeks. These results remained consistent and robust across various climates, latitudinal gradients, and valid pixel proportions. We also revealed discrepancies in the inter-annual variability of LSP between the two products. These disparities in phenological metrics directly lead to systematic uncertainties in the measurements of temperature sensitivity. Furthermore, urban phenology disparities primarily arise from the different phenology definitions employed by the two products. Standardizing the definition of phenology metrics extraction from remote sensing data is crucial to the comprehensive understanding of phenological responses to urban environments, which thus provides referencing resources for studying how future environmental changes affect vegetation in natural ecosystems.

Airborne particulate matter inhalation bioaccessibility: A review of methodological aspects.

Research has consistently linked exposure to particulate matter (PM) with adverse health outcomes, including cardiovascular and pulmonary morbidity and mortality. Understanding the mechanisms by which PM leads to these effects on human health is crucial for developing effective mitigation strategies. One aspect of PM research that has gained increasing attention in the past few years is the bioaccessibility of inhaled PM-bound pollutants that have potential to cause adverse health effects. To assess the bioaccessibility of PM-bound pollutants, such as polycyclic aromatic hydrocarbons, phthalate esters, organophosphorus flame retardants and metal(loid)s, simulated lung fluids (SLF) are used as a tool to mimic the conditions in the human respiratory system. In addition to different SLF, various extraction methodologies and experimental conditions (e.g., incubation period, solid to liquid ratio, and pH) have been employed to extract the bioaccessible part of these pollutants, though there is not yet a standardised procedure to do so. This review aims to critically evaluate existing inhalation bioaccessibility methodologies and explore their connection with PM characteristics. More research is needed, and a standardised procedure should be implemented to allow the comparation of data between studies. Better in vitro-in vivo relationships need to be established to enhance the feasibility of in vitro bioaccessibility assays as surrogates in human health exposure assessments. Long-term effects of bioaccessible pollutants and any potential synergetic effects between multiple contaminants should also be explored to assess health repercussions more thoroughly.

Modeling of β-Ga2O3 based double gate drain extended junction less FET and its parameter extraction methodology

Abstract A static current model of β—Gallium Oxide (β-Ga2O3) based double gate drain extended junction less field effect transistor (DG-DeJLFET) is proposed. The model consists of two voltage-controlled current sources connected in series. One of the current sources accounts for the operation of the junction less field effect transistor whereas, the other takes care of the drift region current. The model is formulated by considering the mobility degradation caused by moderately elevated electric fields. A parameter extraction methodology for this model is also proposed by considering the dominance of certain parameters in the specific regions of operation. In general, the parameter extraction technique is based on the variation in the device current behavior at moderate electric fields. The proposed parameter extraction methodology is validated by comparing the results with the data obtained from the TCAD simulation.

Methodological tests using Amazonian soil samples for 14C-AMS dating

Abstract Although radiocarbon-accelerator mass spectrometry (14C-AMS) is an important tool for the establishment of soil chronology, its application is challenging due to the complex nature of soil samples. In the present study, chemical extraction methodologies were tested to obtain the most representative age of Amazonian soil deposition by 14C-AMS. We performed acid hydrolysis with different numbers of extractions, as well as treatments combining acid and bases and quartered and non-quartered samples. The ages of the soil organic matter (SOM) fractions were compared to the ages of naturally buried charcoal samples at similar depths. The results showed that the age of the non-hydrolyzable inert fraction of soil was closer to the age of charcoal and older than the ages of humin. It was also observed that the quartering process can influence the results, since the dating of the humin fraction showed variability in the results. Our results are important to provide information about the most suitable method for the 14C-AMS dating of soil samples for paleoenvironment reconstruction studies.

Enhanced Biodiesel Production from <i>Oedogonium sp.</i> and <i>Saccharomyces cerevisiae</i> Using Modified Bligh and Dyer Lipid Extraction Method

The production of alternate renewable, clean fuel sources like biodiesel is being explored in this present study using green algae (Oedogonium sp.) and yeast (Saccharomyces cerevisiae) isolated from mining sites. The study aims to use the newly modified Bligh and Dyer method for extracting lipids from Oedogonium sp. and S. cerevisiae to produce biodiesel. The modified method increased the lipid content to 3.951% for Oedogonium sp and 2.621% for S. cerevisiae compared to Soxhlet apparatus and conventional methods. The biodiesel produced from the lipids is analyzed as per IS1448 standards and is compatible with ASTMD 6751 biodiesel standards. The modified Bligh and Dyer lipid extraction is one of the most efficient lipid extraction methodologies that will contribute to the research in biodiesel production.

Sustainable Supercritical Carbon Dioxide Extraction of Value-Added Lignan from Sesame Meal: Achieving Green Neuroprotection and Waste Valorization by Optimizing Temperature, Solvent, and Pressure

In pursuing sustainable health solutions and growing demand for neuroprotective interventions, the industry demands alternative green extraction technologies to valorize agri-food by-products. This study aimed to develop an optimized supercritical carbon dioxide extraction to isolate sesame meal’s functional compound (lignans) and assess their neuroprotective effects. Extraction was performed at various pressures (2–4 kpsi), temperatures (40–60 °C), co-solvent concentrations (2–25 mol% ethanol), and CO2 collection segments (0–100 NL) to systematically analyze extraction parameters. Extracts were analyzed quantitatively using high-performance liquid chromatography followed by neuroprotective mechanisms analysis through PC12 neural cell and ischemic stroke models. The results showed that adding ethanol enhanced the polarity and density of supercritical CO2, improving the extraction efficiency of polar lignans. Optimal extraction conditions (4 kpsi, 50 °C, 10 mol% ethanol) yielded the highest sesamol, sesamin, and sesamolin. Extracts showed remarkable protective capabilities when subjected to oxygen–glucose deprivation (OGD) conditions simulating ischemic stress, preventing the enhancement of lactate dehydrogenase activity. Relatively low extract concentrations (25–100 μg/mL) significantly mitigated cellular damage induced by short and extended OGD conditions. The findings revealed green extraction methodologies’ capability to transform sesame meal, a food processing waste, into value-added compounds, in line with sustainable development goals for responsible and sustainable food production, particularly SDGs 3, 9, 12, and 13.

Green and Efficient Extraction of Taraxacum kok-saghyz Natural Rubber and Its Structural Analysis

Natural rubber (NR) is in high demand due to its excellent elasticity and physical and mechanical properties, but production is limited and NR is in short supply. There is an urgent need to find new alternative rubber sources. Taraxacum kok-saghyz (TKS), as a green, renewable, widely planted and high content rubber producing plant, has shown broad application prospects. The extraction process is the key to developing efficient, green, and high-purity Taraxacum kok-saghyz Natural Rubber (TKNR) to replace NR in various applications. In this study, TKS roots were processed through repeated boiling to remove inulin, followed by alkaline treatment with potassium hydroxide (KOH) to isolate lignin and facilitate cell wall disruption. Subsequent enzymatic hydrolysis using pectinase and cellulase enabled the dissolution of root-structure carbohydrates, thereby obtained TKNR. Structural characterization of TKNR was conducted and compared with that of NR. The results showed that the combined alkaline and enzymatic extraction methodology effectively isolates TKNR from TKS roots. Structural analysis reveals that TKNR closely resembles NR, having comparable molecular weight and distribution, crystallinity, and crosslinking networks, with both polymers primarily consisting of cis-1,4-polyisoprene.

Comparative assessment of extraction methodologies for hull-less pumpkin seed oil: exploring the functional and nutraceutical potential

Comparative assessment of extraction methodologies for hull-less pumpkin seed oil: exploring the functional and nutraceutical potential

Recovery of Bioactive Constituents from Olive Leaf Pruning Waste of Five Different Cultivars: A Comparison of Green Extraction Techniques to Maximize Health Benefits.

Sustainable agro-waste revaluation is critical to enhance the profitability and environmental footprint of the olive oil industry. Herein, the valorization of olive leaf pruning waste from five cultivars ('Caiazzana', 'Carolea', 'Itrana', 'Leccino', and 'Frantoio') employed green extraction methods to recover compounds with potential health benefits. Sequential ultrasound-assisted maceration (UAM) in n-hexane and ethanol was compared with a compressed fluid extraction strategy consisting of supercritical fluid extraction (SFE) and pressurized liquid extraction (PLE) for their efficiency in recovering distinct classes of bioactives. Chemical profiling by UHPLC-HR-MS/MS (ultra-high-performance liquid chromatography high-resolution tandem mass spectrometry) and GC-MS (gas chromatography mass spectrometry) showed that UAM-EtOH effectively extracted polyphenols (especially luteolin derivatives) and triterpenes (notably maslinic acid), while PLE yielded the highest amount of secoiridoids (e.g., secologanoside). PLE extracts showed better antiradical activities, putatively due to a higher content of flavonoids, secoiridoids, and HCA derivatives than UAM-EtOH ones, as these latter also contained 20-40% (cultivar-dependent) of triterpenes. SFE extracts with a higher concentration of fatty acids and triterpenes showed moderate antioxidant activities but very high AChE inhibition. This study highlights the importance of selecting appropriate extraction methodologies based on the target bioactive compounds and underscores the potential of olive leaf extracts for sustainable bio-products.

Application of Response Surface Methodology for Selective Extraction of Lithium Using a Hydrophobic Deep Eutectic Solvent

Application of Response Surface Methodology for Selective Extraction of Lithium Using a Hydrophobic Deep Eutectic Solvent

Biological Efficiency of Kunzea ericoides Based On Bioactive Compounds and Impact of Extraction

AbstractNew Zealand is known for its diverse population of flora and fauna, of which 80 % are endemic. Māori, the indigenous people of New Zealand, have profound and holistic knowledge of plants and utilize them in medicinal, spiritual, and ecological practices. Among these, kānuka has traditionally been used for medicinal purposes. Prior in vitro studies on kānuka extracts have demonstrated promising antioxidant, antimicrobial, anti‐inflammatory, and antiproliferative properties. These studies further recommend the translation of these findings into new medicines and commercial products. However, a significant knowledge gap regarding their therapeutic potential hinders their application in various industries. A deeper understanding of the biochemical composition of the extract and the mode of interaction to exert its bioactivity in the host is vital for achieving this. Hence, this review evaluates the bioactivities of kānuka in association with its bioactive compounds (polyphenolics and terpenoids) reported in the current literature. Knowing the critical role of extraction methodologies in determining bioactive composition, we highlighted their efficiency in the bioactivities of kānuka.

Extraction and response surface methodology optimization of tungsten and molybdenum from spent fluidized catalytic cracking catalysts

Extraction and response surface methodology optimization of tungsten and molybdenum from spent fluidized catalytic cracking catalysts

Green Extraction of Bioactives from Curcuma longa Using Natural Deep Eutectic Solvents: Unlocking Antioxidative, Antimicrobial, Antidiabetic, and Skin Depigmentation Potentials.

This study evaluates the efficiency of 20 Natural Deep Eutectic Solvents (NADES) formulations for extracting curcuminoids and other bioactive compounds from turmeric and emphasize their ability to preserve and enhance antioxidant, antimicrobial, antidiabetic, and skin depigmentation effects. The NADES formulations, prepared using choline chloride (ChCl) combined with sugars, carboxylic acids, glycerol, amino acids, urea, polyols, and betaine, were assessed for their extraction efficiency based on the total phenolic content and curcumin concentration. Fourier transform infrared spectroscopy was employed to characterize the synthesized NADES and confirm their chemical composition. Bioactivity evaluations included antioxidant assays (ABTS and DPPH), antidiabetic tests (α-amylase inhibition), antimicrobial assays, and skin depigmentation (tyrosinase inhibition). The results demonstrated that NADES significantly enhanced the extraction efficiency and bioactive properties of turmeric extracts compared to water as a conventional green solvent. NADES 18 (ChCl/1,2-propanediol/water 1:1:1) and NADES 19 (glycerol/betaine/water 1:1:3) exhibited the highest extraction yields, with curcumin concentrations of 30.73 ± 1.96 mg/g and 31.70 ± 2.02 mg/g, respectively, outperforming water (26.91 ± 1.72 mg/g), while NADES 17 (ChCl/1,2-propanediol/water 0.5:3:0.5:5) and NADES 20 (glycerol/lysine/water 1:1:3) exhibited the most potent antioxidant activity. Furthermore, NADES 14 (ChCl/lactic acid/water 1:2:5) demonstrated the strongest tyrosinase inhibition (98.7%), supporting its potential for skin-brightening applications, including notable α-amylase inhibition exceeding 90%. This study aligns with the principles of green chemistry, as NADES are effective and sustainable solvents for natural product extraction. The presenting benefits of improved extraction efficiency and enhanced bioactivities position NADES as a promising and eco-friendly approach for developing efficient bioactive compound extraction methodologies.

Effect of Different Papain Concentrations on Yield and Quality of Tuna Eye Oil

Graphical Abstract Highlight Research Innovative Use of By-Products: The study explores the use of tuna eye by-products, a rich source of docosahexaenoic acid (DHA), to reduce reliance on imported fish oil and promote sustainable utilization of fishery waste. Enhanced Extraction Methodology: Enzymatic extraction using papain at optimal concentrations significantly improves the yield and quality of tuna eye oil, achieving up to six times higher yield compared to other methods. Nutritional and Quality Benefits: The extracted oil demonstrated low Index of Atherogenicity (IA) and Index of Thrombogenicity (IT), indicating its potential as a heart-healthy dietary supplement, with DHA and EPA concentrations well preserved. Environmental and Safety Advantages: The enzymatic process is solvent-free, minimizing environmental impact and ensuring consumer safety, while also addressing challenges posed by extended sample storage during the COVID-19 pandemic. Abstract Docosahexaenoic acid (DHA) is an essential omega-3 fatty acid, a major component of the human frontal cortex performing a significant role in the fetal brain and retinal development. Deficiency of this component, especially in fetuses, infants, and young children, triggers poor brain neurodevelopment and cognitive impairment. Compulsion of fish oil rich in DHA fulfilled by imports reaching 9,124,579 kg in 2021. In the interim, utilization of potential by-products (tuna’s eyes) as a source of DHA has not been piloted on account of some constraints, one of which is yield that has not been maximized. Enzymatic oil extraction is considered green extraction which is safer and produces higher yields than conventional extraction using high temperatures and chemical solvents. The purpose of this study was to determine the optimal concentration of papain in enzymatic extraction to obtain the highest possible yield of tuna eye oil and the quality of extracted tuna eye oil. The best results were obtained from the extraction with papain enzyme 1% at 55°C for 1 hour, giving an optimal yield. The best yield produced was 8.59 ± 0.69%, or six times higher than cold extraction (centrifugation) without enzyme addition (1.41 ± 0.07%). Adding enzyme concentration up to 1% resulted in increased yield, decreased dark color, decreased viscosity, and improved oxidation quality. The study found that the Index of Atherogenicity (IA) and Index of Thrombogenicity (IT) values fell within low ranges 0.38-0.40 and 0.20-0.21, respectively. Heating during the enzymatic hydrolysis process (55°C) for 1 hour did not significantly alter the percentage of PUFA, and especially DHA remained well preserved.

Inter-laboratory ring test for environmental DNA extraction protocols: implications for marine megafauna detection using three novel qPCR assays

The comparability of methods applied to environmental DNA (eDNA) samples across laboratories remains a significant challenge for biodiversity monitoring on a global scale. Performance differences between protocols can jeopardize effective conservation strategies across regions and focal species. To address potential discrepancies amongst four international partners within a collaborative eDNA initiative, an inter-laboratory comparison (i.e., ring test) was conducted to compare efficiencies of established DNA extraction methodologies based on 39 eDNA samples. Each laboratory contributed eight to eleven samples collected throughout the North-East Atlantic and the Mediterranean Sea near sperm whales, porbeagle sharks, basking sharks, bottlenose dolphins and common dolphins. After lysis, aliquots were exchanged between laboratories before subsequent DNA extraction using each facility’s preferred method. Extracts were returned to the lysates’ respective laboratories of origin for measurements of total DNA concentration, as well as quantitative PCR using three novel species-specific assays for marine megafauna. Our findings revealed similar concentrations of total DNA, yet a significant reduction in extraction performance for targeted qPCR reactions by one laboratory, who has therefore modified their extraction method to be used for the remainder of this project. Overall, detection success differed based on the target taxa with sharks being less often detected (and at lower concentrations) than marine mammals. Significant interaction effects were found between combinations of laboratories and species, suggesting a link between extraction protocols and variable environmental conditions. Our study serves as a foundational step towards establishing reproducible practices that are crucial for the success of multinational eDNA projects to enable comparable results.

The Salivary Transcriptome: A Window into Local and Systemic Gene Expression Patterns.

Saliva, a readily available and noninvasive biofluid, has emerged as a promising source for gene expression studies, offering a window into both local and systemic gene expression patterns. The salivary transcriptome and miRNome hold valuable information about the physiological and pathological processes occurring in the oral cavity and throughout the body.This chapter delves into the potential of saliva as a noninvasive sampling method, exploring its utility in gene expression profiling for various applications. It provides an overview of the components contributing to the salivary transcriptome and discusses the challenges associated with salivary RNA analysis. We highlight the applications of salivary gene expression studies in biomarker discovery for oral and systemic diseases.While discussing various saliva collection techniques, here we focus on the procedure for RNA extraction, including microRNA (miRNA) from the OMNIgene™ SALIVA DNA and RNA device, OMR-610 (DNA Genotek Inc., Ottawa, Ontario, Canada). Herein, we provide the detailed methodologies for RNA extraction for salivary transcriptomics and the miRNome, thus providing a resource for researchers interested in leveraging the diagnostic and prognostic potential of saliva for personalized medicine and precision health initiatives.

Harnessing the Power of Black Rice Anthocyanins: A Review in Context of Extraction and Chromatographic Techniques

Black rice, a well‐known grain for its anthocyanin‐rich pigmentation and nutritional benefits, has gained significant attention in scientific research. Anthocyanins, flavonoid pigments responsible for the distinctive coloration of black rice, offer potent antioxidant and health‐promoting properties. Extraction and chromatographic techniques play pivotal roles in isolating and analyzing these valuable compounds. This review comprehensively examines the extraction methodologies, encompassing traditional solvent extraction and advanced techniques such as ultrasound‐assisted extraction and supercritical fluid extraction. In addition, chromatographic techniques, including high‐performance liquid chromatography (HPLC), high‐speed countercurrent chromatography (HSCCC), and preparative HPLC (Prep‐HPLC) are demonstrated in detail for precise identification and quantification of anthocyanins in black rice.

Silk fibroin as a potential candidate for bone tissue engineering applications.

Silk fibroin (SF), a pivotal biomaterial, holds immense promise for diverse applications within the realm of bone tissue engineering. SF is an ideal scaffold material with exceptional biocompatibility, mechanical robustness, biodegradability, and bioactivity. A plethora of investigations have corroborated SF's efficacy in supporting bone tissue repair and regeneration. This comprehensive review delves into the structural attributes, physicochemical characteristics, and extraction methodologies of SF. Moreover, it elucidates the strides taken in harnessing SF across a spectrum of forms, including films, hydrogels, scaffolds, electrospun fibers, and composites for bone tissue engineering applications. Moreover, the application bottleneck of SF as a bone repair material is highlighted, and its development prospects and potential biomedical applications are also presented in this review. We expect that this review can inspire the broad interest of a wide range of readers working in the fields of materials science, tissue engineering, biomaterials, bioengineering, and biomedicine.