Extraction Method Research Articles

Unlocking sustainable lithium: A comparative life cycle assessment of innovative extraction methods from brine

The surging demand for lithium, driven by the widespread adoption of electric vehicles and renewable energy storage systems, underscores the urgent need to develop sustainable lithium extraction methods. This study presents a comprehensive Life Cycle Assessment Using the TRACI method to evaluate and compare the environmental impacts of solvent extraction, adsorption, nanofiltration, and membrane electrolysis as direct lithium extraction methods for recovering lithium from brine to produce lithium carbonate. In terms of global warming, the carbon dioxide emission for each process was determined as follows: solvent extraction emits 52.7 kg CO2eq/kg of lithium carbonate, adsorption emits 47.9 CO2eq/kg of lithium carbonate, nanofiltration emits 17.7 kg CO2eq/kg of lithium carbonate, and membrane electrolysis emits 80.57 kg CO2eq/kg of lithium carbonate. As a result, the nanofiltration process emerges as the most environmentally friendly method, offering a promising solution to the environmental challenges of lithium extraction. In contrast, the membrane electrolysis process has the highest environmental impact.

Intelligent Abstractive Summarization of Scholarly Publications with Transfer Learning

Intelligent abstractive text summarization of scholarly publications refers to machine-generated summaries that capture the essential ideas of an article while maintaining semantic coherence and grammatical accuracy. As information continues to grow at an overwhelming rate, text summarization has emerged as a critical area of research. In the past, summarization of scientific publications predominantly relied on extractive methods. These approaches involve selecting key sentences or phrases directly from the original document to create a summary or generate a suitable title. Although extractive methods preserve the original wording, they often lack the ability to produce a coherent, concise, and fluent summary, especially when dealing with complex or lengthy texts. In contrast, abstractive summarization represents a more sophisticated approach. Rather than extracting content from the source, abstractive models generate summaries using new language, often incorporating words and phrases not found in the original text. This allows for more natural, human-like summaries that better capture the key ideas in a fluid and cohesive manner. This study introduces two advanced models for generating titles from the abstracts of scientific articles. The first model employs a Gated Recurrent Unit (GRU) encoder coupled with a greedy-search decoder, while the second utilizes a Transformer model, known for its capacity to handle long-range dependencies in text. The findings demonstrate that both models outperform the baseline Long Short-Term Memory (LSTM) model in terms of efficiency and fluency. Specifically, the GRU model achieved a ROUGE-1 score of 0.2336, and the Transformer model scored 0.2881, significantly higher than the baseline LSTM model, which reported a ROUGE-1 score of 0.1033. These results underscore the potential of abstractive models to enhance the quality and accuracy of summarization in academic and scholarly contexts, offering more intuitive and meaningful summaries.

Analysis of the Impact of Clusters on Productivity of Multi-Fracturing Horizontal Well in Shale Gas

Shale gas reservoirs with nanoporous media have become one of the primary resources for natural gas development. The nanopore diameters of shale reservoirs range from 5 to 200 nm, with permeability ranging from 1 × 10−9 to 1 × 10−6 μm2. The natural gas production from shale gas reservoirs is low, necessitating the use of multi-stage hydraulic fracturing in horizontal wells. Segmented multi-cluster perforation fracturing is an effective method for shale gas extraction in these wells. The number of clusters significantly impacts the productivity of horizontal wells. Therefore, it is essential to analyze the impact of cluster numbers on fracture productivity in shale gas reservoir development. In this study, the equivalent flow resistance method was applied to establish a productivity model for multi-stage hydraulic fracturing horizontal wells in shale gas reservoirs considering diffusion and slip. An approximate analytical solution was obtained, and the effects of cluster length, diffusion coefficient, and fracture network permeability on productivity were analyzed. The results show that gas production gradually increases with the increase in the number of clusters and cluster length. However, as the number of clusters increases, the interference between clusters leads to a decrease in the productivity of individual clusters. As the fracture permeability, fracture network permeability, and diffusion coefficient increase, shale gas production also gradually increases. The permeability of the fracture network has the greatest impact on productivity. These research results are beneficial for the design of clusters in horizontal well fracturing and are of great importance for the development and production of shale gas reservoirs.

Applying Subcritical Water Extraction to Obtain Bioactive Compounds and Cellulose Fibers from Brewer Spent Grains

Of the three types of waste generated in beer processing, brewer’s spent grain (BSG) is the most abundant and has a high potential for valorization. In this work, defatted BSG (DB) was subjected to an extraction process with subcritical water at different temperatures to obtain extracts rich in phenols and the cellulosic fractions, which were also purified by using hydrogen peroxide (H2O2). The results showed that the dry extracts obtained at 170 °C were richer in phenolics (24 mg Gallic Acid Equivalent (GAE) g−1 DB), but with lower antioxidant capacity (71 mg DB·mg−1 2,2-diphenyl-1-pikryl-hydrazyl). This extract also showed the highest antibacterial potential against L. innocua (80 mg·mL−1) and E. coli (140 mg·mL−1) than those obtained at lower temperatures. The purification of cellulose from the treated residues, using hydrogen peroxide, revealed that DB is a limited source of cellulose material since the bleached fractions showed low yields (20–25%) and low cellulose purity (42–71%), even after four bleaching cycles (1 h) at pH 12 and 8% H2O2. Despite this, the subcritical water extraction method highlights the potential of a simple process as a technological option to convert underutilized side streams like beer bagasse into added-value, potential ingredients for innovative food and pharmaceutical applications.

Chemical Composition, Antioxidant, Antibacterial, and Hemolytic Properties of Ylang-Ylang (Cananga odorata) Essential Oil: Potential Therapeutic Applications in Dermatology

Background/Objectives: This study investigates the chemical composition, antioxidant, antibacterial, and hemolytic properties of ylang-ylang (Cananga odorata) essential oil, with a focus on its potential therapeutic applications for dermatological diseases and the importance of transforming such bioactive properties into a stable, safe, and effective formulation. Methods/Rsults: Essential oils were extracted from flowers harvested in northern Grande Comore using hydro distillation at three different distillation times to examine the impact on yield and quality. Gas chromatographic analysis identified a complex mixture of compounds, including linalool, geranyl acetate, and benzyl benzoate. Antioxidant activity was assessed using DPPH, FRAP, TAC, and beta-carotene bleaching inhibition assays, revealing significant radical scavenging capabilities, with DPPH IC50 varying between 1.57 and 3.5 mg/mL. Antibacterial activity was tested against Escherichia coli, Staphylococcus aureus, Bacillus subtilis, and Pseudomonas aeruginosa, showing promising inhibition zones and minimum inhibitory concentrations. Hemolytic tests indicated varying degrees of red blood cell damage, emphasizing the need for careful concentration management in therapeutic applications. Molecular docking studies highlighted potential therapeutic targets for dermatological conditions, identifying high binding affinities for specific compounds against proteins involved in acne, eczema, and psoriasis. Conclusions: This comprehensive analysis underscores the potential of ylang-ylang essential oil (YEOs) as a natural alternative for antimicrobial treatments and dermatological applications, with its success dependent on optimized extraction methods and precise formulation to reduce cytotoxic effects. A formulation approach is crucial to ensure controlled release, improve bioavailability, and minimize skin irritation.

Optimization of Ultrasound-Assisted Enzymatic Extraction Conditions on Yield, DPPH Antioxidant Activity, and Gel Strength of Agar from Gracilaria fisheri

ABSTRACT This study investigated the effect of ultrasound-assisted enzymatic extraction (UAEE) conditions: solid-to-water ratio (1:50–1:100), ultrasonic power (296–506 W), and temperature (40–60°C) on key criteria (responses) of Gracilaria fisheri agar. Response surface methodology resulted in accurate quadratic models for predicting responses. Non-linear (quadratic and interaction) effects of UAEE conditions significantly (p < 0.05) influenced the responses. Optimal conditions (solid-to-water ratio of 1:98, ultrasonic power of 506 W, and temperature of 60°C) produced 32.02% agar yield, 58.05% DPPH antioxidant activity, and 83.48 g/cm2 gel strength, aligning with predictions. This research establishes an efficient agar extraction method with controllable qualities from red seaweed.

Algorithm for extracting the normal cross-section parameters of multiple ball screw shaft ball tracks based on an optical micrometer measurement system

Abstract The accurate and efficient measurement of the normal cross-section parameters of multiple ball screw shaft spiral ball tracks are pivotal for ensuring quality control in ball track machining. Given the intricate nature of the ball screw shaft spiral ball track, balancing the accuracy and efficiency of the normal cross-section parameters measurement is a significant challenge. In this study, we present a method to calculate two core parameters, arc radius and contact angle. The method consists of four parts: the automatic axial cross-section separation method, the arc symmetric extraction method, the spiral transformation method, and the parameter algorithm based on the weighted least squares method. The experimental and simulation results validated the effectiveness of our method. Compared with the traditional axial measurement and transformation (AMT) method, our algorithm reduced the errors in arc radius and contact angle by up to 13.9 µm and 4.77°, respectively, and improved the accuracy by up to 78.34% and 85.04%. Compared with the traditional AMT methods and directly normal measurement method, the measurement time of our algorithm was reduced by up to 1565 s and 3475 s, respectively, and the efficiency was improved by up to 71.01% and 84.51%, respectively.

A study of short-term wind power segmentation forecasting method considering weather on ramp segments

The short-term fluctuation of wind power can affect its prediction accuracy. Thus, a short-term segmentation prediction method of wind power based on ramp segment division is proposed. A time-series trend extraction method based on moving average iteration is proposed on the full-time period to analyze the real-time change characteristics of power time-series initially; secondly, a ramp segment extraction method based on its definition and identification technique is proposed based on the results of the trend extraction; and a segmentation prediction scheme is proposed to lean the power prediction under different time-series: the LightGBM-LSTM is proposed for the non-ramping segment using point prediction, and the CNN-BiGRU-KDE is proposed for probabilistic prediction of ramp segments. From the results, this ramp segment definition and identification technique can effectively identify the ramp process of wind power, which makes up for the misidentification and omission of the classical climbing event definition; meanwhile, the segment prediction scheme not only meets the prediction accuracy requirements of the non-ramping segment, but also provides the effective robust information for the prediction of the ramping period, which offers reliable reference information for the actual wind farms. In particular, it is well adapted to wind power prediction under extreme working conditions caused by ramping weather, which is a useful addition to short-term wind power prediction research.

Green and sustainable recovery of polyphenols, flavonoids, alkaloids, and pigments from green tea leaves: Comparative analysis of Soxhlet, accelerated solvent, and supercritical fluid extraction techniques

The growing interest in green tea extracts for their applications in pharmaceutical, food, and cosmetic industries underscores the need for environmentally sustainable extraction methods. This study presents optimized strategies for the green recovery of bioactive compounds from Gun powder green tea leaves using Soxhlet extraction, accelerated solvent extraction, and supercritical fluid extraction techniques. By varying extraction solvents (supercritical CO2, ethanol, water, and their combinations) and temperatures (from 35 to 140 °C), high yields of polyphenols, flavonoids, alkaloids, and pigments were achieved. Key bioactive compounds extracted in significant quantities included caffeine (23.8 mass%), chlorophyll A (8.1 mg/g), chlorophyll B (0.7 mg/g), carotenoids (0.4 mg/g), epicatechin (7.7 mass%), catechin gallate (4.6 mass%), and epigallocatechin-3-gallate (30.2 mass%). The extract obtained in optimized processes demonstrated potent antioxidant activity (IC50 up to 88 μg/mL), strong antimicrobial activity (including methicillin-resistant Staphylococcus aureus- MRSA) with MIC up to 0.06 mg/mL, and selective anticancer activity against colon cancer cells. The presented findings provide a theoretical basis and technical guidance for enhancing the sustainable concentration of natural bioactive compounds, promoting their use in various industrial applications.

A prospective randomized study on the efficacy of real-time dynamic navigation in deep horizontal mandibular third molar extractions

PurposeThis study aimed to evaluate the clinical efficacy of applying real-time dynamic navigation (RDN) in the extraction of deep horizontal mandibular impacted third molars, hypothesizing that RDN reduces surgical time and minimizes the risk of injury to adjacent anatomical structures.MethodsA prospective study was conducted on 160 patients aged between 18 and 37 years with deep horizontal impaction of the mandibular third molar. The participants were randomly assigned to either the experimental group (receiving RDN-assisted extractions) or the control group (undergoing traditional extraction methods). Preoperative planning utilized cone beam computed tomography (CBCT) and Mimics software for the accurate localization and segmentation of impacted teeth. Parametric data were analysed via an independent t test for intergroup comparisons, and significance was set to p < 0.05.ResultsIn the experimental group, an average of 11 ± 1 min was required for preoperative planning via RDN, which was not required in the control group. The setup of the navigation system took an average of 4 ± 1 min in the experimental group and 0 min in the control group. The experimental group demonstrated a significantly shorter average surgical time (22 ± 3 min) than did the control group (36 ± 3 min). The differences in the preoperative design time, surgical time, and complication rates between the two groups were statistically significant (p = 0.005). Additionally, the RDN group reported no complications related to adjacent tooth damage or nerve injury.ConclusionThe precision, safety, real-time guidance of RDN supports its use in complicated dental extractions, which would introduce a new era of oral and maxillofacial surgery.Graphical

Valorization of water hyacinth: Efficient extraction of nanofibrillated crystals using ultrasound-assisted TEMPO oxidation and their application in flexible piezoelectric films

This study presents an efficient extraction of nanocellulose crystals (CNCs) and nanofibers (CNFs) through ultrasound-assisted TEMPO oxidation method using deep-processed heavy metal-containing calabash as raw material. The extraction method, integrating TEMPO-mediated oxidation and ultrasound techniques, enhanced the yield of CNCs and CNFs. The results demonstrate that CNCs yielded 63 %, with a carboxyl content of 1.27 mmol/g, while CNFs yielded 31 %, with a carboxyl content of 1.21 mmol/g. CNCs and CNFs exhibited excellent mechanical properties, with CNCs having an average length of 214.4 nm, average diameter of 2.72 nm, and a length-to-diameter ratio of 78.8. CNFs had an average length of 437.8 nm, average diameter of 5.7 nm, and a length-to-diameter ratio of 76.8. X-ray diffraction (XRD) results showed crystallinity of 87.1 % for CNCs and 81.2 % for CNFs. The thermal stability of the fibers was confirmed up to 230℃. The film prepared by combining 10 % PVA with 90 % CNC exhibited a tensile strength of 32.11 MPa, Young's modulus of 2027.1 MPa, and could generate a maximum voltage of 0.83 V. This study provides an effective pathway for the value-added utilization of deep-processed calabash and highlights the broad application prospects of the composite film in the field of flexible sensors.

Evaluation of Annona muricata Linn Leaves Extracts from Maceration and Ultrasonic-Assisted Methods for Anticancer Activity on HLFa Cells

Non-small cell lung cancer (NSCLC) is a deadly kind of cancer that contributes significantly to the global cancer mortality rate. It is distinguished by a significant level of malignancy and unfavourable prognosis. The molecular pathways responsible for tumour invasion and migration in NSCLC are not fully understood, despite their widespread occurrence and significant consequences. Moreover, the ability of cancer cells to withstand the effects of chemical treatments presents a substantial obstacle in the creation of successful treatment approaches for NSCLC. Annona muricata Linn (A. muricata) is known to possess powerful anticancer bioactive components. A. muricata extracts have demonstrated significant therapeutic potential among a wide range of botanical compounds. However, the specific molecular interactions of the plant have not yet been revealed. This study aims to evaluate the anticancer potential of A. muricata leaves extracts on the NSCLC cell line and compare the efficacy of two different extraction methods, namely maceration extraction (ME) and ultrasonic-assisted extraction (UAE). Results showed that ME demonstrated significantly higher antioxidant activity compared to UAE, with respective percentages of 81.4% and 29.4%. However, the UAE extract demonstrated more pronounced cytotoxic effects on the NSCLC cell line (HLFa) with an IC50 value of 139.6 µg/ml, indicating a stronger antiproliferative effect on cancer cell. Both ME and UAE extracts reduced nitrite release in HLFa cell supernatants, with the ME extract showing superior activity. Treatment with ME and UAE also resulted in the activation of Caspase3/7, indicating the induction of apoptosis in HLFa cells compared to the untreated control. The extracts and Cisplatin differ approximately 0.3-fold in caspase 3/7 activation though it was not statistically significant. This activation suggests that both extraction methods effectively initiate the apoptotic cascade which is crucial for the elimination of cancer cells. Furthermore, the UAE extract significantly reduced BCL-2 mRNA levels (p&lt;0.05). The significant reduction in BCL-2, a protein that prevents apoptosis reflect the extract’ ability to modulate key apoptotic regulators with the most significant activity when UAE extracts were used. In summary, A.muricata leaves extracts obtained through both ME and UAE methods exhibited promising anticancer effects against NSCLC, with UAE extracts exhibiting superior activity. These findings pave the way for further investigations into the use of A.muricata in cancer treatment and the development of new therapeutic agents based on its properties.

Modified rat pup cerebrospinal fluid collection method

BackgroundCerebrospinal fluid (CSF) reflects biochemical changes in the brain due to its direct contact with brain interstitial fluid, making it a valuable tool for diagnosing and monitoring disease progression and therapeutic effectiveness in clinical practice. However, collecting CSF in animal studies, particularly from small animals like rat pups or mice, poses significant challenges. New methodAfter attempting various reported protocols, we encountered difficulties in consistently obtaining sufficient CSF from rat pups (P7-P42). Consequently, we modified these methods and developed a protocol with controllable and precise parameters for each step, enhancing reproducibility across different researchers. ResultsThe newly developed method enables rapid, single-operator, and reproducible CSF extraction while ensuring high-quality (the absorbance of the “quality control solution” at 415 nm < 0.05 AU, an indicator of oxyhemoglobin contamination for the collected CSF samples) and high-yield samples (33 ± 2.128 μL for P7 pups, 34.10 ± 2.747 μL for P8 pups, 36.67 ± 3.997 μL for P9 pups, 36.90 ± 1.946 μL for P10 pups, 35.11 ± 3.285 μL for P10 hypoxic-ischemic brain damage (HIBD) pups and 51.70 ± 5.256 μL for P42 pups, respectively). Comparison with existing methodsUnlike existing methods of CSF extraction in rat pups, our protocol has reproducible capillary pipette pulling parameters, controllable CSF quality indexes, and can be operated by a single person with high yield in a short time. ConclusionsThis paper provides a step-by-step comparison and discussion of the CSF collection process, establishing a method that enables a single operator to collect CSF rapidly, consistently, sufficiently, and with controlled quality.

Modular Point-of-Need Tropane Alkaloid Detection at Regulatory Levels: Combining Solid-Liquid Extraction from Buckwheat with a Paper-Immobilized Liquid-Phase Microextraction and Immuno-Detection in Interconnectable 3D-Printed Devices.

Contamination with tropane alkaloids in cereals is expected to increase globally. However, current identification tools (e.g., liquid chromatography-mass spectrometry) for tropane alkaloids are time-consuming and expensive. Furthermore, their miniaturized alternatives lack sensitivity and robustness. Therefore, there is a pressing need for inexpensive and effective screening methods. Here, an on-site applicable modular workflow for tropane alkaloid detection in buckwheat is presented. The modular workflow combines paper microfluidics and interconnectable 3D-printed sample preparation tools and was evaluated for different tropane alkaloids, including atropine and scopolamine. Furthermore, integration with an indirect competitive lateral flow immunoassay (icLFIA) for atropine detection at relevant levels was demonstrated. In the modular workflow, to minimize matrix coextraction, tropane alkaloids were extracted from the milled buckwheat cereals by a mixture of alkaline aqueous and immiscible organic solvents (extraction recoveries: 66-79%). The tropane alkaloids were subsequently concentrated with a newly developed paper-immobilized liquid-phase microextraction (PI-LPME, extraction recoveries: 34-60%, concentration factor to immobilized solution in paper: 60-108×). After the PI-LPME, with an integrated 3D-printed setup, the tropane alkaloids were directly eluted (elution recoveries: 83-93%) and detected with the icLFIA. Digital read-out of the icLFIA, by employing a hand-held reader, enabled semiquantification of atropine (IC50 = 0.56 ng mL-1 in standard solutions). The modular workflow was validated by analyzing 24 blank and spiked buckwheat cereal samples with 5 and 10 μg kg-1 atropine. A cutoff value was established with an estimated false negative rate of 1% and estimated false positive rate of 0.68%. Therefore, the modular workflow can aid in fast, inexpensive, and on-site atropine detection by nonexperts, and when integrated with a scopolamine-specific icLFIA expanded toward scopolamine detection. Moreover, the developed sample extraction and concentration method (PI-LPME) is suitable for the analysis of many other compounds with pH-dependent polarity.

A Procedure for Solid-Phase Extractions Using Metal-Oxide-Coated Silica Column in Lipidomics.

Lipid enrichment is indispensable for enhancing the coverage of targeted molecules in mass spectrometry (MS)-based lipidomics studies. In this study, we developed a simple stepwise fractionation method using a titanium- and zirconium-dioxide-coated solid-phase extraction (SPE) silica column that separates neutral lipids, phospholipids, and other lipids, including fatty acids (FAs) and glycolipids. Chloroform was used to dissolve the lipids, and neutral lipids, including steryl esters, diacylglycerols, and triacylglycerols, were collected in the loading fraction. Second, methanol with formic acid (99:1, v/v) was used to retrieve FAs, ceramides, and glycolipids, including glycosylated ceramides and glycosylated diacylglycerols, by competing for affinity with the Lewis acid sites on the metal oxide surface. Finally, phospholipids strongly retained via chemoaffinity interactions were eluted using a solution containing 5% ammonia and high water content (45:50 v/v, 2-propanol:water), which canceled the electrostatic and chelating interactions with the SPE column. High average reproducibility of <10% and coverage of ∼100% compared to those of the non-SPE samples were demonstrated by untargeted lipidomics of human plasma and mouse brain, testis, and feces. The advantage of our procedure was showcased by characterizing minor lipid subclasses, including dihexosylceramides containing very long-chain polyunsaturated FA in the testis, monogalactosyl and digalactosyl monoacylglycerols in feces, and acetylated and glycolylated derivatives of gangliosides in the brain that were not detected using conventional solvent extraction methods. Likewise, the value of our method in biology is maximized during glycolipidome profiling in the absence of neutral lipids and phospholipids that cover more than 80% of the chromatographic peaks.

The construction of international wetland urban ecological security pattern coupled with MSPA and ESF.

Creating an ecological security pattern is crucial for balancing the sustainable development of areas where human activities and the natural environment intersect. Using Hefei, an internationally recognized Wetland City, as a case study, we extracted ecological sources through ecological service function (ESF) analysis and morphological spatial pattern analysis (MSPA) core area connectivity analysis. Based on these ecological sources, we developed an ecological resistance surface system and identified ecological corridors and nodes using circuit theory. The findings are as follows: (1) Ecological source areas: The primary ecological sources in Hefei are located in the water bodies, forested areas, and scattered grasslands in the central and eastern parts of the city. This ecological source area covers 978.96 km2, which constitutes 8.55% of the city's total area. (2) Ecological corridors: Hefei contains 43 ecological corridors with a total length of 940.3km, averaging 21.87km each. These corridors are crucial for maintaining ecological connectivity and facilitating species movement. (3) Ecological nodes: There are 13 significant ecological nodes in Hefei, including 6 ecological obstacle points and 7 ecological pinpoints. These nodes play a vital role in supporting ecological processes and ensuring habitat connectivity. (4) Evaluation metrics: The α and β values for the source identification method that integrates MSPA with ecological service functions were 2.15 and 0.8, respectively, which are higher than those of the control group. Conversely, the γ-value was 0.18, lower than that of the control group. These results indicate that the combined ecological source extraction method provides significant advantages in terms of ecological corridor integrity, connectivity, and ecological flow management.

체육전공 대학생의 전공만족도와 무경계진로태도가 진로탄력성에 미치는 영향

Objectives The purpose of this study is to investigate the impact of major satisfaction and boundary-less career attitude of college students majoring in physical education on career elasticity, suggest measures to promote employment of college students majoring in physical education, and provide basic data necessary for employment guidance for college students majoring in physical education. It is in Methods 450 students from the sports departments of three universities located in Daegu and North Gyeongsang Province were selected and sampled using the convenience extraction method, and 427 questionnaires were used for the final analysis. Descriptive statistical analysis, frequency analysis, correlation analysis, and multiple regression analysis were conducted using the Windows SPSS Ver 22.0 statistical program. Results First, positive and negative correlations were found between the major satisfaction perceived by college students majoring in physical education, their boundaryless career attitude, and career elasticity. Second, it was found that college students majoring in physical education had a positive effect on perceived major satisfaction and a negative effect on major dissatisfaction. Third, the borderless career attitude perceived by college students majoring in physical education was found to have a positive effect on the sub-factors of career elasticity. Conclusions If we can increase the level of major satisfaction and boundary-less career attitude of college students majoring in physical education, it is believed that this can increase the career elasticity necessary to promote employment of college students majoring in physical education, and it can be useful for leaders in guiding college students majoring in physical education toward employment. You will be able to use it.

LDAGM: prediction lncRNA-disease asociations by graph convolutional auto-encoder and multilayer perceptron based on multi-view heterogeneous networks

BackgroundLong non-coding RNAs (lncRNAs) can prevent, diagnose, and treat a variety of complex human diseases, and it is crucial to establish a method to efficiently predict lncRNA-disease associations.ResultsIn this paper, we propose a prediction method for the lncRNA-disease association relationship, named LDAGM, which is based on the Graph Convolutional Autoencoder and Multilayer Perceptron model. The method first extracts the functional similarity and Gaussian interaction profile kernel similarity of lncRNAs and miRNAs, as well as the semantic similarity and Gaussian interaction profile kernel similarity of diseases. It then constructs six homogeneous networks and deeply fuses them using a deep topology feature extraction method. The fused networks facilitate feature complementation and deep mining of the original association relationships, capturing the deep connections between nodes. Next, by combining the obtained deep topological features with the similarity network of lncRNA, disease, and miRNA interactions, we construct a multi-view heterogeneous network model. The Graph Convolutional Autoencoder is employed for nonlinear feature extraction. Finally, the extracted nonlinear features are combined with the deep topological features of the multi-view heterogeneous network to obtain the final feature representation of the lncRNA-disease pair. Prediction of the lncRNA-disease association relationship is performed using the Multilayer Perceptron model. To enhance the performance and stability of the Multilayer Perceptron model, we introduce a hidden layer called the aggregation layer in the Multilayer Perceptron model. Through a gate mechanism, it controls the flow of information between each hidden layer in the Multilayer Perceptron model, aiming to achieve optimal feature extraction from each hidden layer.ConclusionsParameter analysis, ablation studies, and comparison experiments verified the effectiveness of this method, and case studies verified the accuracy of this method in predicting lncRNA-disease association relationships.

Validation of Serum Tetrahydrocannabinol Assay and Its Clinical Application

Abstract Background The widespread use of marijuana across all age groups in the United States, driven by the legalization of recreational and medical cannabis, has underscored the need for accurate measurement of tetrahydrocannabinol (THC) and its metabolites in blood specimens. This requirement spans both legal and medical contexts, prompting the development of precise diagnostic tools. Methods We developed a high-throughput liquid chromatography-tandem mass spectrometry (LC-MS/MS) assay, utilizing a straightforward protein precipitation extraction method to quantify THC and its metabolites: THC, 11-OH-THC, THC-COOH, cannabidiol (CBD), and THC-COOH glucuronide. The assay was rigorously validated for precision, linearity, stability, carryover, and quality assurance to ensure its reliability and accuracy for clinical use. Results Precision studies demonstrated a coefficient of variation ranging from 1.7% to 4.9%. The analytical measurement range was established at 1-100 ng/mL for THC, CBD, and 11-OH-THC, 5-500 ng/mL for THC-COOH, and 10-1000 ng/mL for THC glucuronide, accommodating the broad spectrum of THC/metabolite concentrations observed in our patient cohort. Carryover from all analytes were negligible (&amp;lt;0.01%). Sample stability was confirmed for up to two weeks at -20°C and through three freeze-thaw cycles. Despite a median THC concentration of 5 ng/mL in a limited sample size (N=44), high concentrations of THC and its metabolites correlated with trauma-related incidents and a history of polysubstance abuse in emergency department admissions. Conclusions The LC-MS/MS assay offers superior sensitivity and specificity compared to traditional immunoassays for cannabinoid detection, effectively distinguishing between THC and its metabolites. Its implementation will offer an advanced approach for analyzing the prevalence and clinical implications of THC and metabolite levels in various patient populations, including trauma, pediatric patients, and organ transplant candidates.

Comprehensive Analysis of Complex Copy Number Variations in the Plasmodium falciparum Genome via Long-Read Sequencing: Implications for Antimalarial Resistance and Broad Genomic Insights

Abstract Introduction/Objective The genome of Plasmodium falciparum, characterized by a high AT content and a propensity for copy number variations (CNVs), presents a model for understanding how genomes adapt to stress. Our research focused on the prevalence and distribution of CNVs highlights long-read sequencing as a tool for detecting complex structural variants in other models. Methods/Case Report P. falciparum parasites were cultured and treated with DSM1 and aphidicolin that induce replication stress. Long-read sequencing was conducted using the Oxford Nanopore Technology Minion, with an emphasis on an optimizing DNA extraction method for preserving intact chromosomes. Visualization of CNVs, including tandem and inverted duplications, was achieved through a custom R Shiny application that allowed both quantitative and qualitative assessments. Results (if a Case Study enter NA) Long read sequencing identified an enrichment of multiple CNV types in treated samples, with a significant enrichment of inverted duplications as well as other types of structural variants. Aphidicolin and DSM1-treated samples demonstrated significant accumulation of these variations compared to controls (2.0 and 5.6-fold, respectively with a p value of &amp;lt; 0.0001 in both treatment groups). These occurred mainly in core genomic regions that do not contain variable gene copies. An increase in the number of inverted duplications may be related to stress response to the treatment and may be a potential adaptive mechanism of the parasite. Our manual single-read visualization technique made it possible to visualize the structure of various CNV types, which provides unique insight on CNVs as they arise in single genomes. Conclusion We hypothesize that inverted duplications represent stalled replication forks, and we are currently assessing their frequency in replicating and non-replicating cells. This study highlights the role of long-read sequencing in detecting complex genomic structures in P. falciparum, which may influence the parasite’s resistance to drug treatment. These findings not only advance our understanding of malaria pathology but also aid our comprehension of how cancer cells might react to drug-induced stress and the mechanisms behind CNV formation in neoplastic cells.