Different extractable pools of Cd and Pb in agricultural soil under amendments: Water-soluble concentration sensitively indicates metal availability.

Identification of the most appropriate chemically extractable pool for evaluating Cd and Pb availability remains elusive, hindering accurate assessment on environmental risks and effectiveness of remediation strategies. This study evaluated the feasibility of European Community Bureau of Reference (BCR) sequential extraction, Ca(NO3)2 extraction, and water extraction on assessing Cd and Pb availability in agricultural soil amended with slaked lime, magnesium hydroxide, corn stover biochar, and calcium dihydrogen phosphate. Moreover, the enriched isotope tracing technique (112Cd and 206Pb) was employed to evaluate the aging process of newly introduced Cd and Pb within 56 days' incubation. Results demonstrated that extractable pools by BCR and Ca(NO3)2 extraction were little impacted by amendments and showed little correlation with soil pH. This is notable because soil pH is closely linked to metal availability, indicating these extraction methods may not adequately reflect metal availability. Conversely, water-soluble concentrations of Cd and Pb were markedly influenced by amendments and exhibited strong correlations with pH (Pearson's r: -0.908 to -0.825, P < 0.001), suggesting water extraction as a more sensitive approach. Furthermore, newly introduced metals underwent a more evident aging process as demonstrated by acid-soluble and water-soluble pools. Additionally, water-soluble concentrations of essential metals were impacted by soil amendments, raising caution on their potential effects on plant growth. These findings suggest water extraction as a promising and attractive method to evaluate Cd and Pb availability, which will help provide assessment guidance for environmental risks caused by heavy metals and develop efficient remediation strategies.

Molecularly imprinted polymers-coated magnetic covalent organic frameworks for efficient solid-phase extraction of sulfonamides in fish.

In this study, covalent organic frameworks (COFs) were grown in situ on magnetic nitrogen-doped graphene foam (MNGF), and the resulting composite of COFs-modified MNGF (MNC) was wrapped by molecularly imprinted polymers (MNC@MIPs) for specifically capturing SAs. A magnetic solid phase extraction (MSPE) method for SAs was established using MNC@MIPs with good magnetic responsiveness. The adsorption performance of MNC@MIPs was superior to that of non-molecularly imprinted polymers (MNC@NIPs), with shorter adsorption/desorption time and higher imprinting factors. A high-efficiency SAs analytical method was developed by fusing HPLC and MNC@MIPs-based MSPE. This approach provides excellent precision, a low detection limit, and wide linearity. By analyzing fish samples, the feasibility of the approach was confirmed, with SAs recoveries and relative standard deviations in spiked samples in the ranges of 77.2-112.7 % and 2.0-7.2 %, respectively. This study demonstrated the potential use of MNC@MIPs-based MSPE for efficient extraction and quantitation of trace hazards in food.

Extraction and characterization of valuable compounds from chicken sternal cartilage: Type II collagen and chondroitin sulfate.

Type II collagen (Col II) and chondroitin sulfate (CS) are the main macromolecules in the extracellular matrix. This study investigated the characteristics of Col II and CS obtained from chicken sternal cartilage (CSC) via enzymatic hydrolysis for various treatment times. For Col II and CS, the highest efficiency of enzymatic hydrolysis was achieved after 24 and 6 h of treatment, respectively. The average molecular weights were α1 chain-130 kDa, ß chain-270 kDa for Col II, and 80.27 kDa for CS. Fourier transform infrared spectroscopy revealed that the Col II samples maintained their triple-helical structure and that the predominant type of CS was chondroitin-4-sulfate. Scanning electron microscopy revealed that the Col II and CS samples possessed fibrillar and clustered structures, respectively. This study suggests that collagen and CS obtained from CSC can be used as promising molecules for application in food and pharmaceutical industries.

Facile synthesis of magnetic ionic covalent organic framework and dispersive magnetic solid phase extraction of aromatic amino acid oxidation products in thermally processed foods.

Aromatic amino acid oxidation products (AAAOPs) are newly discovered risk substances of thermal processes. Due to its significant polarity and trace level in food matrices, there are no efficient pre-treatment methods available to enrich AAAOPs. Herein, we proposed a magnetic cationic covalent organic framework (Fe3O4@EB-iCOF) as an adsorbent for dispersive magnetic solid-phase extraction (DMSPE). Benefiting from the unique charged characteristics of Fe3O4@EB-iCOF, AAAOPs can be enriched through electrostatic interaction and π-π interactions. Under the optimal DMSPE conditions, the combined HPLC-MS/MS method demonstrated good linearity (R2 ≥ 0.990) and a low detection limit (0.11-7.5 µg·kg-1) for AAAOPs. In addition, the method was applied to real sample and obtained satisfactory recoveries (86.8 % âˆ¼ 109.9 %). Especially, we applied this method to the detection of AAAOPs in meat samples and conducted a preliminarily study on its formation rules, which provides a reliable basis for assessing potential dietary risks.

Simultaneous extraction of tocochromanols and flavan-3-ols from the grape seeds: Analytical and industrial aspects.

Grape processing generates large amounts of by-products, including seeds rich in hydrophilic and lipophilic antioxidants. This study demonstrates, for the first time, that subjecting grape seeds to a single ultrasound-assisted extraction (UAE) with aqueous ethanolic solutions yields both flavan-3-ols and tocochromanols in the final extract. Notably, the water content in ethanol significantly influences the extractability of tocochromanols more than flavan-3-ols. Solid-to-solvent ratios of 1:50 to 1:2 were tested for both analytical and industrial applications. A sustainable analytical approach for recovering flavan-3-ols and tocochromanols using 60% and 96.4% ethanol extractions was validated and employed to profile nineteen genotypes of lesser-studied interspecific grape crosses (Vitis spp.). Different genotypes showed a wide range of concentrations of tocopherols (1.6-6.3 mg/100 g), tocotrienols (1.0-17.4 mg/100 g), and flavan-3-ols (861-9994 mg/100 g). This indicated that the genetic background and maturity of the plant material are crucial factors from an industrial perspective due to the initial concentration of bioactive compounds. Finally, the study also discussed the fundamental aspects of hydrophobic antioxidant extractability from the lipid matrix with aqueous ethanol solutions and the limitations of the workflow, such as the non-extractable tocochromanols and their esters and the losses of these lipophilic antioxidants during extraction.

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.

Current status of technological advancement of ultrasound processing in the food industry and its SWOT analysis.

The use of conventional food processing techniques has almost vanished due to increase in demand with respect to time, thus opening new avenues for emerging technologies. Ultrasound (US) is a rapid, multifaceted, promising, and noninvasive green technology. It has attracted the attention of both industrial experts and scientists for its probable use in food processing and preservation. Using US, fully reproducible food processes can be accomplished in seconds or minutes with increased reliability, minimal processing cost, streamlined manipulation, elevated clarity to the end product, and expending only a fragment of the time and energy commonly required by conventional processes.This review emphasizes on the applications of ultrasound in different food sectors along with its certain limitations. Several operations such as microbial inactivation, enzyme inactivation, extraction, emulsification and fractionation in dairy industries, thermo-sonication in fruit juices have been discussed in detail. The US extracted dietary fiber consisted of increased amount of dietary fiber and trace elements in comparison to alkaline method. US initiate rapid creaming of milk fat, decreasing flavor loss and energy requirements thus enhancing the quality of end product. SWOT analysis has been carried out to pinpoint the strengths, weaknesses, opportunities and threats of sonication in various food industries.

Immediate implant placement in damaged extraction sockets: a systematic review and meta-analysis of randomized controlled trials.

OBJECTIVES: The aim of this study was to observe whether immediate implant placement (IIP) into damaged extraction sockets is a successful modality for treating hopeless teeth that require extraction. DATA SOURCE: An electronic search was carried out through four databases (PubMed/MEDLINE, Web of Science, Scopus, and ScienceDirect) to identify randomized controlled trials (2013-2023) to understand whether IIP in damaged sockets is a successful treatment. The focus question was, 'In a patient with a hopeless tooth that needs extraction with the indication for dental implant treatment, is IIP in damaged extraction sockets, compared to undamaged sockets or healed sites, an effective method for the replacement of hopeless teeth and achieving a favorable clinical result?' The risk of bias was appraised and a meta-analysis using random effect was applied. Five studies with 135 patients and 138 implants were included. The implant survival rate was 100% for all studies and period evaluated; the pink esthetic score (PES) scores had no statistically significant result for all articles that evaluated this parameter; the soft tissue changes was reported by two studies: one found no significant differences and the other showed that the test group experienced reduced soft tissue loss at the 1-year evaluation (measured with digital intraoral scanners); other two studies assessed the marginal bone loss, presenting no differences between groups. The meta-analysis showed homogeneity between the studies. There was an equilibrium among the groups in the various studies included, and age tended to be lower in the test group. The buccal bone tissue and pink esthetic score showed favoritism for the test group but without statistical significance. CONCLUSION: This study suggests that IIP in the presence of buccal bone defects can achieve comparable clinical and radiological outcomes to traditional methods in the short term of the limited studies available. The buccal aspect is not possible to be evaluated through radiographs. Bone regeneration was essential to reach optimal results. It is important to emphasize that IIP requires adherence to rigorous criteria to ensure functionally acceptable results.

Extraction of camptothecin and 10-hydroxycamptothecin from Camptotheca acuminata fruits by natural deep eutectic solvent.

A natural deep eutectic solvent-based ultrasound-assisted simultaneous extraction (NADES-UAE) of camptothecin (CPT) and 10-hydroxycamptothecin (10-HCPT) was established. The 1.31 mg of CPT and 1.66 mg of 10-HCPT were obtained from each gram of the fruit powder of Camptotheca acuminata under the optimum conditions with a water content of 20%, a liquid-solid ratio of 12 mL/g and an ultrasound time of 20 min. The recovery efficiencies of CPT and 10-HCPT after AB-8 resin enrichment were 70.5% and 74.8%, respectively. The stronger interaction between NADES3 which was screened from 12 kinds of NADES and target components compared with methanol or water was demonstrated using molecular dynamics simulation. Moreover, the recovered NADES3 could be reused at least 4 times. The present research provided an efficient, environment-friendly, and sustainable method for extracting and recovering CPT and 10-HCPT from the fruits of C. acuminata.

SCIP: A scalable, reproducible, and open-source pipeline for morphological profiling image cytometry and microscopy data.

Imaging flow cytometry (IFC) provides single-cell imaging data at a high acquisition rate. It is increasingly used in image-based profiling experiments consisting of hundreds of thousands of multi-channel images of cells. Currently available software solutions for processing microscopy data can provide good results in downstream analysis, but are limited in efficiency and scalability, and often ill-adapted to IFC data. In this work, we propose Scalable Cytometry Image Processing (SCIP), a Python software that efficiently processes images from IFC and standard microscopy datasets. We also propose a file format for efficiently storing IFC data. We showcase our contributions on two large-scale microscopy and one IFC datasets, all of which are publicly available. Our results show that SCIP can extract the same kind of information as other tools, in a much shorter time and in a more scalable manner.

Graph neural pre-training based drug-target affinity prediction.

Computational drug-target affinity prediction has the potential to accelerate drug discovery. Currently, pre-training models have achieved significant success in various fields due to their ability to train the model using vast amounts of unlabeled data. However, given the scarcity of drug-target interaction data, pre-training models can only be trained separately on drug and target data, resulting in features that are insufficient for drug-target affinity prediction. To address this issue, in this paper, we design a graph neural pre-training-based drug-target affinity prediction method (GNPDTA). This approach comprises three stages. In the first stage, two pre-training models are utilized to extract low-level features from drug atom graphs and target residue graphs, leveraging a large number of unlabeled training samples. In the second stage, two 2D convolutional neural networks are employed to combine the extracted drug atom features and target residue features into high-level representations of drugs and targets. Finally, in the third stage, a predictor is used to predict the drug-target affinity. This approach fully utilizes both unlabeled and labeled training samples, enhancing the effectiveness of pre-training models for drug-target affinity prediction. In our experiments, GNPDTA outperforms other deep learning methods, validating the efficacy of our approach.

Game-Based Assessment of Peripheral Neuropathy Combining Sensor-Equipped Insoles, Video Games, and AI: Proof-of-Concept Study.

BACKGROUND: Detecting peripheral neuropathy (PNP) is crucial in preventing complications such as foot ulceration. Clinical examinations for PNP are infrequently provided to patients at high risk due to restrictions on facilities, care providers, or time. A gamified health assessment approach combining wearable sensors holds the potential to address these challenges and provide individuals with instantaneous feedback on their health status. OBJECTIVE: We aimed to develop and evaluate an application that assesses PNP through video games controlled by pressure sensor-equipped insoles. METHODS: In the proof-of-concept exploratory cohort study, a complete game-based framework that allowed the study participant to play 4 video games solely by modulating plantar pressure values was established in an outpatient clinic setting. Foot plantar pressures were measured by the sensor-equipped insole and transferred via Bluetooth to an Android tablet for game control in real time. Game results and sensor data were delivered to the study server for visualization and analysis. Each session lasted about 15 minutes. In total, 299 patients with diabetes mellitus and 30 with metabolic syndrome were tested using the game application. Patients' game performance was initially assessed by hypothesis-driven key capabilities that consisted of reaction time, sensation, skillfulness, balance, endurance, and muscle strength. Subsequently, specific game features were extracted from gaming data sets and compared with nerve conduction study findings, neuropathy symptoms, or disability scores. Multiple machine learning algorithms were applied to 70% (n=122) of acquired data to train predictive models for PNP, while the remaining data were held out for final model evaluation. RESULTS: Overall, clinically evident PNP was present in 247 of 329 (75.1%) participants, with 88 (26.7%) individuals showing asymmetric nerve deficits. In a subcohort (n=37) undergoing nerve conduction study as the gold standard, sensory and motor nerve conduction velocities and nerve amplitudes in lower extremities significantly correlated with 79 game features (|R|>0.4, highest R value +0.65; P<.001; adjusted R2=0.36). Within another subcohort (n=173) with normal cognition and matched covariates (age, sex, BMI, etc), hypothesis-driven key capabilities and specific game features were significantly correlated with the presence of PNP. Predictive models using selected game features achieved 76.1% (left) and 81.7% (right foot) accuracy for PNP detection. Multiclass models yielded an area under the receiver operating characteristic curve of 0.76 (left foot) and 0.72 (right foot) for assessing nerve damage patterns (small, large, or mixed nerve fiber damage). CONCLUSIONS: The game-based application presents a promising avenue for PNP screening and classification. Evaluation in expanded cohorts may iteratively optimize artificial intelligence model efficacy. The integration of engaging motivational elements and automated data interpretation will support acceptance as a telemedical application.

Establishment of appropriate conditions for the efficient determination of multiple mycotoxins in tea samples and assessment of their drinking risks.

Conditions were determined for rapid, convenient, and efficient determination of 16 common mycotoxins in tea samples. Mycotoxins in tea leaves and tea infusion samples were extracted using solid-liquid extraction/liquid-liquid extraction combined with ultrasonic-assisted extraction. The extraction solvent was 2-butanone/ethyl acetate (9/1 v/v) with 0.1 % formic acid. The established conditions enabled the analysis of these mycotoxins by ultra-high-performance liquid chromatography tandem mass spectrometry (UHPLC-MS/MS) in 5.5 min. In addition, HPLC with a temperature-controlled fluorescence detector was able to simultaneously determine 8 mycotoxins with fluorescent properties in 10 min without derivatization. Aflatoxin M1 (2.15 and 3.01 µg/kg), fumonisin B2 (198.89 µg/kg), and zearalenone (87.54 µg/kg) could be detected in commercially available pu-erh tea, green tea, and black tea products, and their total transfer rates from the products to brewed tea infusions were 64.08-65.13 %, 90.59 %, and 25.99 %, respectively. The risks of drinking mycotoxins from these tea infusions mostly showed low levels of concern.

A Rare Case of Gastric Phytobezoar (Diospyrobezoar) in a Healthy Adult.

Phytobezoars are solid masses of indigestible plant material and are a common type of gastrointestinal bezoar, with varying incidences globally. These bezoars typically form from the ingestion of high-fiber fruits and vegetables and are associated with factors such as decreased gastric acid production and delayed gastric emptying. We present a case of a 35-year-old healthy man with recurrent upper abdominal pain, nausea, a rolling ball sensation in the abdominal region, and a history of consuming unripe persimmons. Imaging revealed the presence of phytobezoars in the stomach, leading to unsuccessful endoscopic attempts at removal. Laparoscopic extraction was eventually performed successfully after failed conservative management. The case highlights the rarity of diospyrobezoars, a subtype of phytobezoars formed from persimmon ingestion, and the challenges in their management. Surgical intervention, particularly laparoscopic extraction, can be effective but carries risks such as surgical site infections. Comprehensive care involving diagnostic imaging, non-surgical interventions, and surgical techniques is crucial for the successful management of phytobezoars. Phytobezoars, though relatively common, present unique diagnostic and management challenges, especially when formed from specific dietary factors such as persimmons. Understanding their epidemiology, clinical manifestations, and treatment options, including the role of laparoscopic surgery, is essential for optimizing patient outcomes and minimizing complications such as surgical site infections.

Ultrasound-assisted enzymatic extraction of jujube (Ziziphus jujuba Mill.) polysaccharides: Extraction efficiency, antioxidant activity, and structure features.

This study investigated the effect of ultrasound-assisted enzymatic extraction (UAEE) on the extraction efficiency, antioxidant activity, and structural properties of jujube polysaccharide (JPS), with hot water extraction (HWE), ultrasound-assisted extraction (UAE), and enzymatic-assisted extraction (EAE) serving as controls. Optimal extraction conditions were determined through a multi-index weighted scoring method that comprehensively accounted for yield, duration, and antioxidant activity. Results demonstrated that the JPS yield obtained by UAEE at 22/33 kHz was 10.5 % to 16.3 % higher than those achieved by the other methods, significantly enhancing antioxidant activity. Monosaccharide composition analysis revealed that UAEE increased the content of key mono-sugars in JPS. Additionally, assessments of molecular weight distribution, zeta potential, and rheological properties showed that UAEE reduced the molecular weight and apparent viscosity of JPS, resulting in a looser structural configuration. These structural modifications were observed in scanning electron microscope (SEM) images, which revealed a filamentous branched morphology in JPS obtained through UAEE. Further observations using the atomic force microscope (AFM) indicated that the polysaccharide chains extracted by UAEE were shorter in length, lower in height, and free from aggregation.

Innovative hierarchical porous hydrophilic molecularly imprinted resin for high-throughput detection of perfluorocarboxylic acids in milk using 96-well plate SPE-LC-MS/MS.

The accumulation of perfluorocarboxylic acids (PFCAs) in environment and foods represents a significant threat to public health due to the long-term ingestion of contaminated food. This study introduces a novel adsorbent, the hierarchical porous hydrophilic molecularly imprinted resin (HPHMIR), which was synthesized by integrating molecular imprinting techniques with hydrophilic resins. The HPHMIR, characterized by its extensive mesoporous structure (average pore width ∼9.71 nm) and favorable imprinting factors (2.6-5.0), facilitates the effective adsorption of PFCAs from complex matrices through multiple interaction mechanisms, including hydrogen bonding and electrostatic interactions. This innovative material was employed in a 96-well plate format for solid-phase extraction (SPE), and combined with LC-MS/MS, a high-throughput method for the determination of PFCAs in milk was developed. The proposed method demonstrated exceptional performance, including excellent linearity (0.48-240 ng mL-1; r ≥ 0.9986), low detection limits (0.04-0.11 ng mL-1), high precision (relative standard deviation ≤ 9.9 %), and satisfactory recovery (75.7-118.1 %). These results highlight the efficacy of the method in extracting trace levels of PFCAs from complicated sample matrices, presenting a promising alternative for monitoring PFCA contamination and advancing public health standards.

X-ray coronary angiography background subtraction by adaptive weighted total variation regularized online RPCA.

Coronary X-ray angiograms (XCA) are widely used in diagnosing and treating cardiovascular diseases. Various structures with independent motion patterns in the background of XCA images and limitations in the dose of injected contrast agent have resulted in low-contrast XCA images. Background subtraction methods have been developed to enhance the visibility and contrast of coronary vessels in XCA sequences, consequently reducing the requirement for excessive contrast agent injections. The current study proposes an adaptive weighted total variation regularized online RPCA (WTV-ORPCA) method, which is a low-rank and sparse subspaces decomposition approach to subtract the background of XCA sequences. In the proposed method, the images undergo initial preprocessing using morphological operators to eliminate large-scale background structures and achieve image homogenization. Subsequently, the decomposition algorithm decomposes the preprocessed images into background and foreground subspaces. This step applies an adaptive weighted total variation (TV) constraint to the foreground subspace to ensure the spatial coherency of the finally extracted coronary vessel images. To evaluate the effectiveness of the proposed background subtraction method, some qualitative and quantitative experiments are conducted on two clinical and synthetic low-contrast XCA datasets containing videos from 21 patients. The obtained results are compared with six state-of-the-art methods employing three different assessment criteria. By applying the proposed method to the clinical dataset, the mean values of the global contrast-to-noise ratio (GCNR), local contrast-to-noise ratio (LCNR), structural similarity index (SSIM), and reconstruction error (RE) are obtained as 5.976, 3.173, 0.987, and 0.026, respectively. These criteria over the low-contrast synthetic dataset were 4.851, 2.942, 0.958, and 0.034, respectively. The findings demonstrate the superiority of the proposed method in improving the contrast and visibility of coronary vessels, preserving the integrity of the vessel structure, and minimizing reconstruction errors without imposing excessive computational complexity. .

Green Technology for Extraction of Bioactive Compounds from Edible Plants.

In modern society, the use of bioactive compounds in various foods and cosmetic industry sectors through the development of general foods, functional foods, cosmetics, customized cosmetics and several pharmaceuticals has become one of the key technological sources. The most critical step in isolating and purifying bioactive compounds from natural plant materials is the extraction process. Over the past five years, there has been a reasonable compromise between economic, social, and environmental requirements, resulting in safer and more efficient traditional and non-traditional extraction methods. This literature review aims to comprehensively review green extraction technologies for the extraction of bioactive compounds from plant materials from 2020 to 2024.

Study on canopy extraction method for narrowband spectral images based on superpixel color gradation skewness distribution features.

BACKGROUND: Crop phenotype extraction devices based on multiband narrowband spectral images can effectively detect the physiological and biochemical parameters of crops, which plays a positive role in guiding the development of precision agriculture. Although the narrowband spectral image canopy extraction method is a fundamental algorithm for the development of crop phenotype extraction devices, developing a highly real-time and embedded integrated narrowband spectral image canopy extraction method remains challenging owing to the small difference between the narrowband spectral image canopy and background. METHODS: This study identified and validated the skewed distribution of leaf color gradation in narrowband spectral images. By introducing kurtosis and skewness feature parameters, a canopy extraction method based on a superpixel skewed color gradation distribution was proposed for narrowband spectral images. In addition, different types of parameter combinations were input to construct two classifier models, and the contribution of the skewed distribution feature parameters to the proposed canopy extraction method was evaluated to confirm the effectiveness of introducing skewed leaf color skewed distribution features. RESULTS: Leaf color gradient skewness verification was conducted on 4200 superpixels of different sizes, and 4190 superpixels conformed to the skewness distribution. The intersection over union (IoU) between the soil background and canopy of the expanded leaf color skewed distribution feature parameters was 90.41%, whereas that of the traditional Otsu segmentation algorithm was 77.95%. The canopy extraction method used in this study performed significantly better than the traditional threshold segmentation method, using the same training set, Y1 (without skewed parameters) and Y2 (with skewed parameters) Bayesian classifier models were constructed. After evaluating the segmentation effect of introducing skewed parameters, the average classification accuracies Acc_Y1 of the Y1 model and Acc_Y2 of the Y2 model were 72.02% and 91.76%, respectively, under the same test conditions. This indicates that introducing leaf color gradient skewed parameters can significantly improve the accuracy of Bayesian classifiers for narrowband spectral images of the canopy and soil background. CONCLUSIONS: The introduction of kurtosis and skewness as leaf color skewness feature parameters can expand the expression of leaf color information in narrowband spectral images. The narrowband spectral image canopy extraction method based on superpixel color skewness distribution features can effectively segment the canopy and soil background in narrowband spectral images, thereby providing a new solution for crop canopy phenotype feature extraction.

Assessment of Third Molar-related Symptoms Affecting Quality of Life using Nepali Version of Oral Health Impact Profile-14: A Descriptive Cross-sectional Study.

INTRODUCTION: Impacted third molars often cause pain, infections, swelling, and functional limitations. This study is an attempt to assess impacted third molars-related symptoms affecting quality of life using standardised Nepali version of oral health impact profile-14 (OHIP-14) questionnaire. METHODS: This descriptive cross-sectional study was conducted at Kathmandu Medical College Teaching Hospital from October 2021 to February 2022 after institutional ethical approval. Patients with impacted third molars were included by convenience sampling technique. Patients with psychiatric illness, taking psychotropic drugs, pregnant, and lactating females were excluded. third molars-related symptoms were recorded in OHIP-14 questionnaire. Data entered in Microsoft Excel sheet were analysed. The findings have been presented as frequency, percent, mean, and standard deviation. The point estimate was calculated at a 95% Confidence Interval. RESULTS: Mean OHIP-14 score of participants was 21.77±11.59. Due to TM, "pain in the mouth" had score of (2.33±1.24) and followed by "uncomfortable experience on eating food" (2.12±2.15). Among seven OHIP-14 dimensions, "physical pain" with two items OHIP3 and OHIP4 had score of 4.53±2.19 implying most participants had "quite a lot" of physical pain due to TM: OHIP3 = 194 (50.2%) and OHIP4 = 183 (47.3%). CONCLUSIONS: Impacted third molars-related symptoms were affecting quality of life of participants.