Extraction Procedure Research Articles

Geometrical morphology and deformation measurement of long-span suspension bridge based on terrestrial laser scanning

Long-span suspension bridges necessitate deformation measurements for proper evaluation and upkeep. However, conventional approaches are unable to collect continuous spatial deformation data, which severely restricts their application in structural research. This paper presents a reliable and efficient method for measuring the deformation of suspension bridges using 3D laser scanning, including planning the scanning route, preprocessing the point cloud data, and extracting the deformation indicators. The method plans the scanning route based on experience and basic path planning principles to achieve both efficiency and precision, preprocesses the point cloud data by 3-stage denoising and curvature-based downsampling to preserve valuable point data better, and then proposes an extraction procedure for different types of deformation indicators. A field test on a typical long-span suspension highway bridge is performed, and the data processing and results extraction details are introduced. The accuracy and consistency of measurement results are discussed to verify the reliability of the proposed approach. The verified data provides useful information for the evaluation and maintenance of the bridge.

Extraction and Purification of Biopolymers from Marine Origin Sources Envisaging Their Use for Biotechnological Applications.

Biopolymers are a versatile and diverse class of materials that has won high interest due to their potential application in several sectors of the economy, such as cosmetics, medical materials/devices, and food additives. In the last years, the search for these compounds has explored a wider range of marine organisms that have proven to be a great alternative to mammal sources for these applications and benefit from their biological properties, such as low antigenicity, biocompatibility, and biodegradability, among others. Furthermore, to ensure the sustainable exploitation of natural marine resources and address the challenges of 3R's policies, there is a current necessity to valorize the residues and by-products obtained from food processing to benefit both economic and environmental interests. Many extraction methodologies have received significant attention for the obtention of diverse polysaccharides, proteins, and glycosaminoglycans to accomplish the increasing demands for these products. The present review gives emphasis to the ones that can be obtained from marine biological resources, as agar/agarose, alginate and sulfated polysaccharides from seaweeds, chitin/chitosan from crustaceans from crustaceans, collagen, and some glycosaminoglycans such as chondroitin sulfate and hyaluronic acids from fish. It is offered, in a summarized and easy-to-interpret arrangement, the most well-established extraction and purification methodologies used for obtaining the referred marine biopolymers, their chemical structure, as well as the characterization tools that are required to validate the extracted material and respective features. As supplementary material, a practical guide with the step-by-step isolation protocol, together with the various materials, reagents, and equipment, needed for each extraction is also delivered is also delivered. Finally, some remarks are made on the needs still observed, despite all the past efforts, to improve the current extraction and purification procedures to achieve more efficient and green methodologies with higher yields, less time-consuming, and decreased batch-to-batch variability.

Pooled prevalence of hypothyroidism among Indian females with infertility: A systematic review & meta-analysis.

Background & objectives Studies suggest hypothyroidism is responsible for female infertility. This review aimed to determine the pooled prevalence of hypothyroidism in Indian infertile women so that hypothyroidism screening can be initiated, and policies are designed for prevalence reduction. Methods Electronic databases including PubMed, Google Scholar and Cochrane library were searched to obtain the relevant articles. Studies that reported the proportion of hypothyroidism in Indian infertile women were selected. Systematic procedures for study selection and data extraction were followed. Each study was evaluated for quality using the Joanna Briggs institute (JBI) critical appraisal checklist. To pool the effect sizes, a random effects model was utilized. Funnel plot and Egger's test were used to assess publication bias. To quantify heterogeneity among studies, I2 statistics were utilized. Subgroup and meta-regression analyses were used to further investigate the heterogeneity of pooled estimates. The sensitivity analysis done whereby each study was excluded in order to examine the influence of that study in the pooled estimate. A P-value of 0.05 or less was considered statistically significant. Results Out of 198 articles, a total of 20 studies involving 2396 cases met the inclusion criteria. The pooled prevalence of hypothyroidism in women with infertility was 28 per cent [95% confidence interval (CI): 20% to 36%] which was highest in Telangana at 62 per cent (n=1; 95% CI 48% to 74%) and lowest in Karnataka at 14 per cent (n=2; 95% CI: 10% to 18%). Interpretation & conclusions Infertile women have high proportion of hypothyroidism, suggesting that screening programmes during diagnostic workup for infertility may provide optimal care. The result of this meta-analysis will help design guidelines and earmark highest prevalence regions to initiate preventive and diagnostic measures for prevalence reduction in future.

Microplastics in urban water cycles: Looking for a more scientific approach for sampling and characterization in wastewater and drinking water treatment plants

Specific campaigns to detect microplastics (MPs) in the urban water cycle were carried out in three drinking water plants and two wastewater treatment plants. A self-designed sampler for MPs detection in water matrices was in this study preliminary validated and then tested in long term campaigns sampling up to 1000 L. Raw drinking water and wastewater show microplastics (MPs) concentrations of 2–11 and of 480–801 MPs/m3, respectively, and MPs removals of 47–78 % and of 84–98 %, correspondingly. Specific roles of chemical and physical conventional processes in microplastics removals were investigated. Solid-liquid separation, flotation and filtration are the main processes for achieving high microplastics removal. Regarding concentrated matrices, MPs concentrations in sludge samples varied in the range of 5000–500,000 MPs/m3. Finally, shapes, size classes and polymers' typologies were investigated in the extracted MPs. The detected sizes are mainly 0.5–0.1 mm in drinking waters while 5–1 mm in wastewaters. Wastewaters were predominated by synthetic fibers (polyester type), while drinking waters were mainly characterized by fragments and the fibers were mostly of natural origin. Finally, the results of this study supported best practices and guidelines for a representative assessment of MPs in water (sampling methods, extraction procedures, characterization and quantification).

A deep learning model for estimating body weight of live pacific white shrimp in a clay pond shrimp aquaculture

This paper presents a novel approach to address the essential challenge of accurately determining the total weight of shrimp within aquaculture ponds. Precise weight estimation is crucial in mitigating issues of overfeeding and underfeeding, thus enhancing efficiency and productivity in shrimp farming. The proposed system leverages image processing techniques to detect individual live shrimp and extract pertinent features for weight estimation within a clay pond environment. Specifically, an automated feed tray captures images of live shrimp, which are then processed using a combination of Detectron2, PyTorch, and CUDA (Compute Unified Device Architecture) for individual shrimp detection. Essential features such as area, perimeter, width, length, and posture are extracted through image analysis, enabling accurate estimation of shrimp weight. An Artificial Neural Network (ANN) model, utilizing these features, accurately predicts shrimp weight with a coefficient of determination (R2) of 94.50% when incorporating all extracted features. Furthermore, our system integrates a user-friendly web application that empowers farmers to monitor shrimp weight trends, facilitating precision feeding strategies and effective farm management. This study contributes a low-cost solution using a deep learning model to estimate the weight of live Pacific white shrimp in clay ponds, enabling daily weight calculations, helping farmers optimize feed quantities, providing shrimp size distribution insights, and reducing the Feed Conversion Ratio (FCR) for greater profitability. The procedure for shrimp feature extraction is also provided, including the calculation of shrimp length and width, as well as shrimp posture classification.

Determination of Quercetin in Iraqi Green Walnut Husk via Green Ionic Liquid-Based Digestion Extraction and Gel Filtration Procedures-Spectrophotometry and Microfluidic Paper-Based Analytical Platform Detection

في هذه الدراسة تم استخلاص ،عزل وتقدير الكيورستين الموجود في قشور الجوز العراقي باستخدام طريقة جديدة تعتمد على الاستخلاص بطريقة الهضم المبنية على استخدام السوائل الايونية و طريقة الترشيح بالجل للفصل المقترنة مع المطيافية الضوئية للتقدير ومن ثم مقارنتها مع تقنية جديدة تسمى تقنية السوائل المايكروية الورقية مستهدفة بناء طريقة اقتصادية، صديقة للبيئة وخضراء. ولقد تم اختيار 1 بيوتيل-3-مثيل ايمادزوليم كلورايد كمذيب اخضر بديل للمذيبات التقليدية بسبب خصائصة الذوبانية .ولقد اظهرت النتائج ان 100 ملغرام من القشورتحتاج الى 15 مل من المذيب و30 دقيقة من الهضم عند درجة75°C كظروف مثلى لاعطاء افضل ناتج للمستخلص بطريقة الهضم مقارنه مع طرق الاستخلاص الاخرى .تحت هذه الظروف المثلى تم عزل الكيورستين باستخدام طريقة الترشيح بالجل وتم التاكد من المركب المعزول باستخدام تقنية كروموتوغرافيا السائل عالية الاداء و اشعة فورية تحت الحمراء .تم تقدير الكيورستين المعزول من المستخلص لونيا ( طريقة كلوريد الالمنيوم) باستخدام طريقتي المطيافية الضوئية و وتقنية السوائل المايكروية الورقية معطيا الخطية لمنحنيات المعايرة لكلتا الطريقيتين بين 10-100 مليغرام / لتر مع معامل ارتباط0.9369 و 0.7917 لكلتا الطريقتين. ومن ثم تم تقدير الفعالية المضادة للاكسدة باستخجام طريقة قوة الاختزال للمركب المعزول مظهرة فعالية مضادة للاكسدة جيدة و بين تحليل التباين (ANOVA) عدم وجود فرق كبير بين تقنية المطيافية الضوئية وتقنية السوائل المايكروية الورقية. كخلاصة يمكن اعتبار المذيب الايوني BMIMCLمذيبا امنا ومناسبا لاستخلاص المركبات النباتية ذات الخواص الطبية وكذلك فان تقنية السوائل المايكروية الورقية اثبتت مقدرتها على التحليل بكفاءة مساوية الى طرق التحليل التقليدية بالاضافة الى خصائصها الخضراء.

Determination of steroid hormones in sea urchins by microwave-assisted extraction and ultrahigh-performance liquid chromatography tandem mass spectrometry

Marine pollution poses significant threats to ecosystems by contaminating habitats and degrading marine life. This involves the need to develop efficient methodologies to evaluate the compounds that affect marine organisms, such as steroid hormones. The study of the presence of these compounds in marine organisms like sea urchins is very interesting given their role as bioindicators because they feed on algae and are constantly in contact with sediments. Given the low concentrations of steroid hormones in marine environments, it is necessary to develop extraction procedures that allow these pollutants to be extracted and preconcentrated before chemical analyses. Of all the extraction methods, microwave-assisted extraction (MAE) has been used for its many advantages compared to traditional extraction techniques, such as easy sample handling or scarce organic solvents use, and for providing very selective extractions. This study presents the novel MAE optimisation for the extraction of 15 hormones, including five oestrogens, three androgens, four progestogens and three glucocorticoids from sea urchin tissues. The extracted hormones were subsequently determined by high-performance liquid chromatography tandem mass spectrometry. To the best of the authors' knowledge, this approach has not been previously developed. To perform extraction optimisation, different variables were studied following factorial experimental designs. The optimised extraction method showed very appropriate analytical parameters, with limits of detection between 0.21 and 20.4 ng·g-1 for the four families of studied steroid hormones, and recovery extractions over 60 % for most target compounds. After optimisation, the analytical methodology was applied to samples of three different sea urchins species (Arbacia lixula, Paracentrotus lividus, Sphaerechinus granularis) caught in different locations around the Gran Canaria island (Canary Islands, Spain). The results showed the great applicability of the optimised methodology and two target hormones, boldenone and prednisolone, which were quantified in different samples and locations. This indicates the potential of sea urchins as bioindicators of the health of marine ecosystems and of anthropogenic contamination.

Prairie Dog Optimization Algorithm with deep learning assisted based Aerial Image Classification on UAV imagery

This study presents a Prairie Dog Optimization Algorithm with a Deep learning-assisted Aerial Image Classification Approach (PDODL-AICA) on UAV images. The PDODL-AICA technique exploits the optimal DL model for classifying aerial images into numerous classes. In the presented PDODL-AICA technique, the feature extraction procedure is executed using the EfficientNetB7 model. Besides, the hyperparameter tuning of the EfficientNetB7 technique uses the PDO model. The PDODL-AICA technique uses a convolutional variational autoencoder (CVAE) model to detect and classify aerial images. The performance study of the PDODL-AICA model is implemented on a benchmark UAV image dataset. The experimental values inferred the authority of the PDODL-AICA approach over recent models in terms of dissimilar measures.

Effects of Passiflora incarnata and Valeriana officinalis in the control of anxiety due to tooth extraction: a randomized controlled clinical trial.

This study evaluated the efficacy of Valeriana officinalis L. and Passiflora incarnata L. to control anxiety, surgical discomfort, and changes in vital signs of patients undergoing extraction of two unilateral third molars. This study is a randomized, triple-blinded clinical trial. Fifty-four patients were allocated into three groups (Valeriana officinalis L., Passiflora incarnata L., and placebo). Anxiety levels were assessed using the State-Trace Anxiety Inventory (STAI) index, surgical discomfort using the QCirDental, and through the measurement of vital signs. The surgical times evaluated were before (T0), during (T1), and after surgery (T2). There was evidence that both Valeriana officinalis L. and Passiflora incarnata L., reduced STAY-S scores between T0 and T2 (p < .05), unlike placebo (p = .129). There was no change in surgical discomfort in all groups over time, and vital signs presented variable results. Phytotherapy drugs showed a reduction in anxiety state compared to the placebo group during third molar extraction procedure. CLINICAL TRIAL REGISTRATION: klRBR-6kcxvrc, March 10, 2022.

Unlocking the potential: Transforming hazardous waste into solid cementitious materials

Incineration fly ash and mineral slag represent hazardous and industrial solid wastes necessitating immediate remediation in China. The liberation and stabilization of heavy metals have erected formidable barriers to their reclamation and repurposing. This study presents a pivotal technology for creating all-solid waste cementitious materials, with the optimal parameters consisting of a dosage of 55.773% incineration fly ash, 38.822% cementitious materials dosage, and 5.405% adhesive powders dosage. Furthermore, a comprehensive evaluation model has been developed to assess the performance of these materials. Several extraction procedure experiments were conducted to investigate the leaching behavior of heavy metals under various leaching scenarios, which suggests the diffusion coefficients of heavy metals under the optimal ratio are all less than 3 × 10–13 m2/s, affirming the effective stabilization and the absence of potential migration risks. The primary mechanisms of solidification involved include ion exchange reactions for charge balance and the encapsulation of precipitates through cementation, both of which contribute to the solidification of heavy metals. The findings will illuminate advanced strategies for reducing waste, enhancing resource efficiency, and promoting environmentally friendly building practices, as well as provide a promising avenue for achieving sustainability goals in construction projects, leading to reduced environmental impact and improved long-term sustainability. The integration of ACM-SW can pave the way for transformative advancements in sustainable building practices, ultimately leading to a more environmentally friendly and resilient built environment.

Optimized analytical strategy based on high-resolution mass spectrometry for unveiling associations between long-term chemical exposome in hair and Alzheimer’s disease

Exposure to environmental pollutants or contaminants is correlated with detrimental effects on human health, such as neurodegenerative diseases. Adopting hair as a biological matrix for biomonitoring is a significant innovation, since it can reflect the long-term chemical exposome, spanning months to years. However, only a limited number of studies have developed analytical strategies for profiling the chemical exposome in this heterogeneous biological matrix. In this study, a systematic investigation of the chemical extraction procedure from human hair was conducted, using a design of experiments and a high-resolution mass spectrometry (HRMS)-based suspect screening approach. The PlackettBurman (PB) design was applied to identify the significant variables influencing the number of detected features. Then, a central composite design was implemented to optimize the levels of each identified significant variable. Under the optimal conditions—15-minute pulverization, 25 mg of hair weight, 40 min of sonication, and a sonication temperature of 35 °C—approximately 32,000 and 15,000 aligned features were detected in positive and negative ion modes, respectively. This optimized analytical procedure was applied to hair samples from patients with Alzheimer's disease (AD) and individuals with normal cognitive function. Overall, 307 chemicals were identified using the suspect screening approach, with 37 chemicals differentiating patients with AD from controls. This study not only optimized an analytical procedure for characterizing the long-term chemical exposome in human hair but also explored the associations between AD and environmental factors.

A porous magnetic hydrogel-metal organic framework composite adsorbent for solvent-assisted magnetic solid-phase extraction and risk assessment of polycyclic aromatic hydrocarbons in food

A porous magnetic composite adsorbent was developed for the solvent-assisted magnetic solid-phase extraction of polycyclic aromatic hydrocarbons (PAHs). The porous magnetic composite adsorbent was created by incorporating a metal-organic framework (MOF), magnetite nanoparticles, and calcium carbonate into alginate beads. The extraction of the analytes was enabled through hydrophobic and π-π interactions between MOF-5, PAHs, and the organic solvent in the micropores. The fabricated adsorbent was characterized and optimized to improve extraction efficiency. Under the optimum conditions, good linearity was achieved with a detection limit in the range of 0.01–0.10 µg L−1. The developed method was successfully applied to extract PAHs from coffee, cocoa, and tea samples for analysis with high-performance liquid chromatography coupled with fluorescence detection (HPLC-FLD). Relative recoveries were obtained in the range of 70.3–96.1 %, with RSDs below 10 %. The developed adsorbent exhibited good stability and the extraction procedure was simple and rapid. The results obtained with the developed method were used to evaluate the incremental lifetime carcinogenic risk (ILCR) in adults from the intake of coffee, cocoa, and tea. Our calculations showed there was no cancer risk to consumers.

Phenolic components from carrot (Daucus carota L.) pomace: Optimizing the extraction and assessing its potential antioxidant and antimicrobial activities

Carrot pomace is a significant agricultural byproduct. Obtained during carrot juice processing. This residue is an appropriate reservoir of constituents with bioactive properties that could be investigated in the development of food constituents and nutritional supplements and in improving the quality and safety of foods. For this purpose, the objective of the present investigation was to extract the polyphenols from carrot pomace utilizing maceration and ultrasound-based extraction (UAE) procedures and to evaluate the antioxidant properties of phenolic constituents. To maximize the extraction of carrot pomace, a response surface approach was used. The optimal mixture of extraction time (A, min), ultrasonication power (B, w), and solvent type (C, v/v) for the highest yield of carrot pomace was found using a three-variable composite rotatable design (CRD). In order to assess different functional groups, Fourier transform infrared spectroscopy was utilized to investigate the extract collected under optimal circumstances. The highest polyphenols (26.53 %) were extracted by ethanol 70 % at 10 min with a sonication power of 250 w. The optimized extract also exhibited significant antioxidant and antimicrobial functions. The total phenolic compounds and scavenging of the DPPH radical were 85 mg GAE/gr and EC50: 55 ± 1 μg/mL, respectively. Together with Staphylococcus aureus, the highest zone of inhibition (12 mm) was identified. Our finding revealed that carrot pomace is an appropriate source of bioactive phenolic constituents, exhibiting antioxidant and antibacterial attributes, and could be applied as a natural preserver for promoting safety and quality properties in food products on an industrial scale.

Sustainable reuse of modified incineration sewage sludge ash (M-ISSA) for stabilization of highly As-contaminated soil

Arsenic (As) is an environmental hazardous contaminant, seriously threatening human health. Chemical activation can effectively enhance As adsorption performance of incinerated sewage sludge ash (ISSA). Through modification, the iron (mainly present as hematite) in the ISSA was rearranged to KFeO2. Based on the results of the present study, addition of modified ISSA (M-ISSA) in contaminated soil had a positive effect on As immobilization. A set of laboratory batch experiments including toxicity characteristic leaching procedure (TCLP), synthetic precipitation leaching procedure (SPLP), and sequential extraction procedure (SEP) were carried out to investigate effects of M-ISSA dosages and curing time on immobilization of As contaminated soil (100, 500, 1000 mg As/kg soil). Results indicated that a higher addition amount of M-ISSA enhanced the effectiveness of stabilization and significantly reduced the As leachability after a stabilization period of 28 d. Particularly, in 1000 mg As/kg soil, M-ISSA reduced the labile As concentration in the TCLP test from 21.45 to 0.73 mg/L and in the SPLP test from 27.75 mg/L to 7.83 mg/L. M-ISSA transformed As in soil to more stable forms that were bounded to amorphous iron hydrous oxides. The number of stable fractions saw a sharp rise from 31% to 60%, when the M-ISSA addition was 5%. Different characterizations were conducted including X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS) and scanning electron microscope (SEM), in order to demonstrate the stabilization behavior and mechanism of As and M-ISSA. The main stabilization mechanism was associated with adsorption and coprecipitation processes. Overall, this study proposed a novel recycling method for ISSA that could be chemically modified into a reliable and efficient additive for the immobilization of As contaminated soil.

Identification of Phytochemicals and Mineral Nutrients of Selected Malaysian Plant Extracts and its Effects on Seed Priming of Maize

Plants contain a variety of phytochemicals, which act as natural bioactive compounds to help plants enhance abiotic tolerance and promote growth. Therefore, plant extracts are considered to have great potential as environmentally friendly biostimulants in sustainable agriculture. This study aimed to identify the phytochemical compounds and quantify nutrients present in three plant extracts, namely Euphorbia hirta, Polygonum minus, and Eleusine indica, as well as to explore the effect on the growth of maize seedlings (Zea mays L.). The plant powder was extracted using methanol, followed by a solid-liquid extraction procedure. The phytocompounds were analyzed by liquid chromatography-mass spectrometry, while mineral nutrients were quantified using inductively coupled plasma. Five concentrations of plant extracts, i.e., 5, 15, 25, 50, and 100%, were designed to evaluate seed germination and priming. The result showed that 53, 45, and 39 phytocompounds were identified from E. hirta, P. minus, and E. indica, respectively, and classified into different chemical groups (such as flavonoids and amino acids) and rich nutrients (for example, N, P, and K). Besides, P. minus and E. hirta extracts with lower concentrations (5 and 15%) showed a positive effect on germination, shoot length and fresh weight, and the Highest concentration (100%) of E. hirta and E. indica extracts exhibited strong toxicity. This study emphasizes that weed extracts containing abundant secondary metabolites and nutrients can be used as natural biostimulants for maize seed priming.

Quantitative determination of phenazepam and its active metabolite in human blood plasma at different extraction procedures

Introduction. The presence of the active metabolite (3-hydroxyphenazepam, 3-OH-PHEN), the wide interindividual variability of the therapeutic effect of phenazepam (PHEN), as well as its active moiety in the blood, determine the relevance of therapeutic drug monitoring (TDM). To do this, the researcher must have an express analytical technique with a wide analytical range, a low limit of quantification (LLOQ), and with robustness with different sample preparation methods.Aim. Development and validation of quantitative methods for PHEN and 3-OH-PHEN in human blood plasma with different sample preparation methods.Materials and methods. The determination of PHEN and 3-OH-PHEN has been performed by high-performance liquid chromatography with tandem mass spectrometry (HPLC-MS/MS). Solid-phase extraction (SPE) and liquid extraction with support (SLE) otherwise called liquid-liquid extraction in the solid phase were used for sample preparation. Metoprolol was utilized as an internal standard (IS). Gradient elution profile between mobile phase A (0.2 % aqueous formic acid) and B (100 % acetonitrile) has been used. Column: Hypersil GOLD® C18, 50 × 2.1 mm, 3.5 μm.Results and discussion. Two methods have been developed for the quantitative determination of PHEN and 3-OH-PHEN in human blood plasma using different sample preparation methods: SPE and SLE. The conditions of chromatographic separation and mass spectrometric detection of the analytes are selected. The following validation characteristics were determined for both methods: selectivity, calibration curve, accuracy, precision, degree of extraction, LLOQ, carry-over effect, matrix factor, stability of standard solutions and analyte in the matrix.Conclusion. The validation results of the developed methods meet the established criteria, which allows them to be used for the quantitative determination of PHEN and 3-OH-PHEN in human blood plasma. The wide analytical range for both methods 1–1000.00 ng/ml allows the use them for pharmacokinetics and bioequivalence studies, as well as in toxicology.

A hybrid approach to extract conceptual diagram from software requirements

Employing rules for the automatic extraction of conceptual diagrams from software requirements has been in practice for some time. However, considering only rules for extraction makes the system complex to handle. Moreover, the rules are predominantly based on the syntactic structure such as Part of Speech tags along with Dependency Grammar of sentences and rarely on semantics. In this paper, we propose to use a probabilistic approach in configuration with the rule-based technique and the Word embeddings to preserve the semantics of the sentence. Hence, reduces the complexity of the extraction procedure. Further, we advocate the use of a divide-and-conquer policy of extraction instead of extracting classes for one entire use case description. We extract the class diagram from small use cases and then merge it to obtain the class diagram. As generated class diagram corresponding to small use cases can be utilized in another similar software design, thus, it increases the scalability and decreases the extraction time. The proposed hybrid approach integrates the knowledge from the experiences. Thus, the proposed approach achieved 90% as F1-score whereas the F1-Score for the existing methods ranged between 79-88%. The proposed hybrid approach also shows a 19.44% reduction in terms of the number of iterations performed to carry out extraction procedures for individual use cases. Hence, reduces the extraction procedure complexity.

Different extraction methods shape the phenolic signature and biological activity of Morinda lucida extracts: A novel source of bioactive compounds preparing functional applications

The extraction of bioactive compounds is based on the application of various extraction techniques. Therefore, the stem and root bark of the plant species Morinda lucida L. were used in this research, while the extraction procedure was performed using three extraction techniques: HAE (homogenizer extraction), UAE (ultrasound extraction) as modern, and MAC (maceration) as conventional extraction technique. The presence of different classes of secondary metabolites was determined using the UHPLC method, while the content of total phenols and flavonoids was determined spectrophotometrically. The biological potential was investigated by in vitro antioxidant and enzyme assays. Different extraction technologies showed significant differences in only two classes of phenols, namely lignans and phenolic acids, which were significantly higher in HAE than in UAE and MAC. These findings highlight the significant effect of stem and bark extracts of M. lucida, opening the way for innovative industrial exploitation of these matrices.

Performance of a NLP Tool for Text Classification from Orthopaedic Operative Reports, Using Data from the Large Network of Clinical Data Warehouses of the West of France: The HACRO-HUGORTHO Project.

Electronic health data concerning implantable medical devices (IMD) opens opportunities for dynamic real-world monitoring to assess associated risks related to implanted materials. Due to population ageing and expanding demands, total hip, knee, and shoulder arthroplasties are increasing. Automating the collection and analysis of orthopedic device features could benefit physicians and public health policies enabling early issue detection, IMD monitoring and patient safety assessment. A machine learning tool using natural language processing (NLP) was developed for the automated extraction of operation information from medical reports in orthopedics. A corpus of 959 orthopaedic operative reports from 5 centres was manually annotated using the Prodigy software® with a strong inter-annotator agreement of 0.80. Data to extract concerned key clinical and procedure information (n= 9) selected by a multidisciplinary group based on the French health authority checklist. Performances parameters of the NLP model estimated an overall strong precision and recall of respectively 97.0 and 96.0 with a F1-score 96.3. Systematic monitoring of orthopedic devices could be ensured by an automated tool, leveraging clinical data warehouses. Traceability of medical devices with implantation modalities will allow detection of implant factors leading to complications. The evidence from real-world data could provide concrete and dynamic insights to surgeons and infectious disease specialists concerning implant follow-up, guiding therapeutic decision-making, and informing public health policymakers. The tool will be applied on clinical data warehouses to automate information extraction and presentation, providing feedback on mandatory information completion and contents of operative reports to support improvements, and thereafter implant research projects.

Dispersive solid phase extraction of some sulfonamide antibiotics from milk combined with dispersive liquid-liquid microextraction

A covalent organic framework based dispersive solid phase extraction was developed for extraction of several antibiotics from raw cow's milk samples. For this purpose, first, the milk proteins were precipitated by zinc sulfate and after centrifugation, the analytes were extracted by the sorbent. Then, the analytes were desorbed by a proper eluent and were more concentrated by a microextraction procedure. The extractant was used for the analysis of the analytes by high-performance liquid chromatography-diode array detector. Based on the results, acceptable extraction recoveries (62–71 %) and sensitive limits of detection and quantification in the ranges of 0.11–0.19 and 0.37–0.63 ng mL−1, respectively, were obtained. The method can analyze the analytes in broad concentration range. The introduced approach was used in the analysis of fifteen raw cow's milk samples. The obtained data showed that all samples were free of the analytes. According to these results, the method can be considered an efficient procedure for extracting the analytes from raw milk samples.