bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comparison of Improved Unidirectional Dual Velocity‐Encoding MRI Methods
Authors: Franco Pamela , Ma Liliana , Schnell Susanne , Carrillo Hugo , Montalba Cristian , Markl Michael , Bertoglio Cristóbal , Uribe Sergio 
Published: June 2022

BackgroundIn phase‐contrast (PC) MRI, several dual velocity encoding methods have been proposed to robustly increase velocity‐to‐noise ratio (VNR), including a standard dual‐VENC (SDV), an optimal dual‐VENC (ODV), and bi‐ and triconditional methods.PurposeTo develop a correction method for the ODV approach and to perform a comparison between methods.Study TypeCase–control study.PopulationTwenty‐six volunteers.Field Strength/Sequence1.5 T phase‐contrast MRI with VENCs of 50, 75, and 150 cm/second.AssessmentSince we acquired single‐VENC protocols, we used the background phase from high‐VENC (VENCH) to reconstruct the low‐VENC (VENCL) phase. We implemented and compared the unwrapping methods for different noise levels and also developed a correction of the ODV method.Statistical TestsShapiro–Wilk's normality test, two‐way analysis of variance with homogeneity of variances was performed using Levene's test, and the significance level was adjusted by Tukey's multiple post hoc analysis with Bonferroni (P < 0.05).ResultsStatistical analysis revealed no extreme outliers, normally distributed residuals, and homogeneous variances. We found statistically significant interaction between noise levels and the unwrapping methods. This implies that the number of non‐unwrapped pixels increased with the noise level. We found that for β = VENCL/VENCH = 1/2, unwrapping methods were more robust to noise. The post hoc test showed a significant difference between the ODV corrected and the other methods, offering the best results regarding the number of unwrapped pixels.Data ConclusionsAll methods performed similarly without noise, but the ODV corrected method was more robust to noise at the price of a higher computational time.Level of Evidence4Technical Efficacy Stage1
Genetic algorithm optimization to minimize fields, maximize power, and inhibit corona of high voltage transmission lines by arranging the conductors
Authors: Al Salameh Mohammed Saleh Hussein , Al‐Hazaimeh Lujain Bilal 
Published: June 2022

AbstractIn this paper, a comprehensive study is presented whereby genetic algorithm optimization (GAO) is used to find the best arrangement of three‐phase high‐voltage transmission line (TL) conductors, that minimizes emitted electric and magnetic fields (EMFs), maximizes power capacity, and avoids corona. Moreover, a financial cost study is conducted in order to show the feasibility of implementing such rearrangement, where construction costs are compared with the impact on a populated area in close proximity to the line. To facilitate applying the procedure of this paper, a detailed description of each step is provided. Both single circuit as well as double circuit transmission lines are considered, and bundled conductors are analyzed. To demonstrate the validity and usefulness of the mathematical formulation and MATLAB computer codes, computed results are compared with measured data where good agreement is observed. To show that using GAO for solving high voltage line problems is an alternative to other robust optimization techniques such as particle swarm optimization (PSO), GAO solutions are compared with PSO solutions. The GAO results are also compared with the unoptimized results, where significant improvements can be seen. Since according to this algorithm, line conductors move freely throughout the solution space in an attempt to find the best solution, it is important to restrict this movement in order to adhere to the separation limits of the transmission line international standards IEC‐71.
Prediction of progression rate and fate of osteoarthritis: Comparison of machine learning algorithms
Authors: Yoo Hyun Jin , Jeong Ho Won , Kim Sung Woon , Kim Myeongju , Lee Jae Ik , Lee Yong Seuk 
Published: June 2022

AbstractAppropriate prediction models can assist healthcare systems in delaying or reversing osteoarthritis (OA) progression. We aimed to identify a reliable algorithm for predicting the progression rate and fate of OA based on patient‐specific information. From May 2003 to 2019, 83,280 knees were collected. Age, sex, body mass index, bone mineral density, physical demands for occupation, comorbidities, and initial Kellgren–Lawrence (K‐L) grade were used as variables for the prediction models. The prediction targets were divided into dichotomous groups for even distribution. We compared the performances of logistic regression (LR), random forest (RF), and extreme gradient boost (XGB) algorithms. Each algorithm had the best precision when the model used all variables. XGB showed the best results in accuracy, recall, F1 score, specificity, and error rates (progression rate/fate of OA: 0.710/0.877, 0.542/0.637, 0.637/0.758, 0.859/0.981, and 0.290/0.123, respectively). The feature importance of RF and XGB had the same order up to the top six for each prediction target. Age and initial K‐L grade had the highest feature importance in RF and XGB for the progression rate and fate of OA, respectively. The XGB and RF machine learning algorithms showed better performance than conventional LR in predicting the progression rate and fate of OA. The best performance was obtained when all variables were combined using the XGB algorithm. For each algorithm, the initial K‐L grade and physical demand for occupation were the greatest contributors with superior feature importance compared with the others.
High tibial osteotomy effectively redistributes compressive knee loads during walking
Authors: De Pieri Enrico , Nüesch Corina , Pagenstert Geert , Viehweger Elke , Egloff Christian , Mündermann Annegret 
Published: June 2022

AbstractThe objectives of this study were to estimate pre‐ and postoperative lower limb kinematics and kinetics and knee intra‐articular forces during gait using musculoskeletal modeling in a cohort of patients with knee osteoarthritis (OA) undergoing high tibial osteotomy (HTO), compare these to controls, and determine correlations between changes in these parameters and Knee Injury and Osteoarthritis Outcome Score (KOOS) subscores after HTO. Sixteen patients with isolated, symptomatic medial compartment knee OA completed pre‐ and postoperative gait analysis (mean follow‐up time: 8.6 months). Sixteen age‐ and sex‐matched asymptomatic volunteers participated as controls. Musculoskeletal modeling was used to evaluate lower limb joint moments and knee contact forces during gait. While HTO had limited influence on sagittal plane kinematics and moments, significant changes in the load distribution at the knee after HTO were observed with a lower postoperative compressive load on the medial compartment during midstance and a higher compressive load on the lateral compartment during early and late stance. Moreover, the lateral shear force in midstance was significantly lower after HTO. Changes in the external knee adduction moment (KAM) did not always coincide with reductions in the knee compressive force in the medial compartment. Biomechanical changes did not correlate with improvements in KOOS subscores. Hence, HTO effectively unloaded the medial compartment by redistributing part of the overall compressive force to the lateral compartment during gait with limited influence on gait function. The KAM may not adequately describe compartmental load magnitude or changes induced by interventions at the compartment level. Clinical trial registration: ClinicalTrials. gov Identifier—NCT02622204. Clinical significance: This study provides important evidence for changes in joint level loads after corrective osteotomy as joint preserving surgery and emphasizes the need for additional biomechanical outcomes of such interventions.
Proportional relationship between periodontal inflamed surface area, clinical attachment loss, and glycated hemoglobin level in patients with type 2 diabetes mellitus on insulin therapy and on oral antidiabetic therapy
Authors: Pattayil Simna , Vadakkekuttical Rosamma Joseph , Radhakrishnan Chandni , Kanakkath Harikumar , Hrishi Thayyil Sivaraman 
Published: June 2022

AbstractBackgroundTreatment of diabetes includes oral antidiabetic drugs (OAD), insulin, or their combinations. Insulin can achieve faster glycemic control and have anabolic action on bone. This study was undertaken to assess the prevalence and severity of periodontitis, and to estimate the proportional relationship between periodontal inflamed surface area, clinical attachment loss, and glycated hemoglobin (HbA1c) level in patients with type 2 diabetes (T2DM) on OAD therapy and on insulin therapy.MethodsThis cross‐sectional study comprised 130 patients with T2DM on OAD therapy (OAD group) and 130 patients with T2DM on insulin therapy (INSULIN group). All patients were assessed for sociodemographic, behavioral characteristics, clinical history, periodontal parameters (bleeding on probing, probing depth, clinical attachment loss [Clinical AL], Oral Hygiene Index‐simplified, plaque index, and periodontal inflamed surface area [PISA]), and biochemical variables (HbA1c, fasting plasma glucose, postprandial plasma glucose).ResultsPrevalence, extent, and severity of periodontitis and PISA were lower in the INSULIN group as compared with the OAD group. A proportional relationship was observed between HbA1c and PISA and between HbA1c and Clinical AL. A unit increase in HbA1c is associated with an increase in PISA of 130.47 mm2 and an increase in Clinical AL of 0.182 mm.ConclusionA proportional relationship was observed between PISA, clinical attachment loss, and HbA1c level in patients with type 2 diabetes mellitus on insulin therapy and OAD therapy. Despite comparable oral hygiene status and glycemic control between the two groups, the periodontal parameters were lesser in the INSULIN group as compared with the OAD group.
Agricultural management affects active carbon and nitrogen mineralisation potential in soils
Authors: Hendricks Sophia , Zechmeister‐Boltenstern Sophie , Kandeler Ellen , Sandén Taru , Diaz‐Pines Eugenio , Schnecker Jörg , Alber Oliver , Miloczki Julia , Spiegel Heide 
Published: June 2022

AbstractBackgroundSoil organic matter (SOM) is important for soil fertility and climate change mitigation. Agricultural management can improve soil fertility and contribute to climate change mitigation by stabilising carbon in soils. This calls for cost‐effective parameters to assess the influence of management practices on SOM contents.AimsThe current study aimed at understanding how sensitively the parameters active carbon (AC) and nitrogen mineralisation potential (NMP) react to different agricultural management practices compared to total organic carbon (TOC) and total nitrogen (Nt). We aimed to gain a better understanding of SOM processes, mainly regarding depth distribution and seasonality of SOM dynamics using AC and NMP.MethodsWe looked mainly at four parameters, namely permanganate oxidisable carbon (AC), nitrogen minerlaisation potential (NMP), total organic carbon (TOC) and total nitrogen (Nt). Data were obtained in five long‐term field experiments (LTEs) testing four management practices: (1) tillage, (2) compost application, (3) crop residue management, and (4) mineral fertilization.ResultsAC was specifically sensitive in detecting the effect of tillage treatment at different soil depths. NMP differentiated between all different tillage treatments in the upper soil layer, it showed the temporal dynamics between the years in the compost LTE, and it was identified as an early detection property in the crop residue LTE. Both AC and NMP detected short‐term fluctuations better than TOC and Nt over the course of two years in the crop residue LTE.ConclusionWe suggest that AC and NMP are two valuable soil biochemical parameters providing more detailed information on C and N dynamics regarding depth distribution and seasonal dynamics and react more sensitively to different agricultural management practices compared to TOC and Nt. They should be integrated in monitoring agricultural long‐term experiments (LTEs) and in field analyses conducted by farmers. However, when evaluating results towards long‐term carbon storage, their sensitivity toward annual fluctuations should be taken into account.
A search of only four key databases would identify most randomized controlled trials of acupuncture: A meta‐epidemiological study
Authors: Guo Qiong , Cheng Yifan , Zhang Chenyang , Yang Huifang , Chen Xia , Wang Xinyi , Yang Liu , Feng Kun , Long Youlin , Shao Zilun , Wang Yutian , Lin Yifei , Liao Ga , Huang Jin , Du Liang 
Published: June 2022

AbstractLittle research has been conducted to assess which specific databases should be searched when performing a systematic review (SR) on acupuncture. The current study aimed to identify key databases and the optimal database combination to retrieve randomized controlled trials (RCTs) on acupuncture for inclusion in SRs. A systematic search for SRs in the field of acupuncture was conducted in order to identify target databases and RCTs were extracted from the SRs that had searched all target databases. The proportions of SRs that had achieved 100%, 95%, or 90% recall of RCTs and the total recall of RCTs in various combinations of target databases were calculated. Sensitivity analysis was performed on those SRs that included 10 or more RCTs. CNKI, WanFang, VIP, PubMed, CENTRAL and Embase were regarded as target databases. A total of 4349 acupuncture RCTs were extracted from 286 SRs. Searching all six target databases retrieved 99.3% of all RCTs while 99.1% were recalled by searching the combination of CNKI, WanFang, PubMed and CENTRAL. There were no significant differences on total recall of RCTs (p = 0.549) or in the proportion of SRs with 90% recall of RCTs (97.2% vs. 97.6%; p = 0.794) between searching the above four and the full six target databases. Most results were similar in the sensitivity analysis. The combined retrieval power of CNKI, WanFang, PubMed and CENTRAL was considered an efficient choice to retrieve acupuncture RCTs included in SRs.
Effect of modified washing process on water usage, composition and gelling properties of grass carp surimi
Authors: Long Kangyuan , Zhang Tonghao , Park Jae W , Park Joodong , Yin Tao 
Published: June 2022

AbstractBACKGROUNDWashing is an essential process in surimi production, from which a large amount of wastewater is generated. Due to the increasing pressure of environmental protection, it is an urgent technical requirement for surimi manufacturers to reduce water usage while maintaining the quality of surimi. In this study, composition, structure and gelling properties of grass carp surimi prepared with a modified washing process (MWP) were investigated. Intermediate dehydration with various compression ratios were utilized between two washing cycles.RESULTSWater usage and wastewater discharge were reduced significantly by 33% and 38%, respectively, when MWP was applied. As the compression ratio increased, composition of fat, cathepsins, transglutaminase and heme proteins in surimi decreased gradually. Yield, protein content and the major protein pattern of surimi were not changed, but surface hydrophobicity gradually decreased. As the compression rate increased to 1:2.0, textural values and water holding capacity of the corresponding surimi gel decreased gradually, while whiteness increased and then remained unchanged. At a higher compression ratio (>1:1.5), aggregated network and excessive free water were observed in the surimi gel. Composition and gelling properties of the MWP surimi with a compression ratio of 1:1.2–1:1.5 were equal to those of the surimi prepared under conventional three‐cycle washing.CONCLUSIONResults indicated that MWP demonstrated its great potential in surimi production by dramatically reducing the usage of cold water and discharge of wastewater without scarifying surimi quality. © 2022 Society of Chemical Industry.
Lipidomics profiling of zebrafish liver through untargeted liquid chromatography‐high resolution mass spectrometry
Authors: da Silva Katyeny Manuela , Iturrospe Elias , van den Boom Rik , van de Lavoir Maria , Robeyns Rani , Vergauwen Lucia , Knapen Dries , Cuykx Matthias , Covaci Adrian , van Nuijs Alexander L. N. 
Published: June 2022

Lipidomics analysis of zebrafish tissues has shown promising results to understand disease‐related outcomes of exposure to toxic substances at a molecular level. However, knowledge about their lipidome is limited, as most untargeted studies only identify the lipids that are statistically significant in their setup. In this work, liquid chromatography‐high resolution mass spectrometry was used to study different aspects of the analytical workflow, that is, extraction solvents (methanol/chloroform/water (3/2/2, v/v/v), methanol/dichloromethane/water (2/3/2, v/v/v) and methanol/methyl‐tert‐butyl ether/water (3/10/2.5, v/v/v), instrumental response, and strategies used for lipid annotation. The number of high‐quality features (relative standard deviation of the intensity values ≤ 10% in the range 103−107 counts) was affected by the dilution of lipid extracts, indicating that it is an important parameter for developing untargeted methods. The workflows used allowed the selection of a dilution factor to annotate 712 lipid species (507 bulk lipids) in zebrafish liver using four software (LipidMatch, LipidHunter, MS‐DIAL, and Lipostar). Retention time mapping was a valuable tool to filter lipid annotations obtained from automatic software annotations. The lipid profiling of zebrafish livers will help in a better understanding of the true constitution of their lipidome at the species level, as well as in the use of zebrafish in toxicological studies.
Blood Flow Turbulence Quantification of Carotid Artery With a High‐Frame Rate Vector Flow Imaging
Authors: Dong Yinghui , Hong Shaofu , Song Di , Liu Mengmeng , Gao Wenjing , Du Yigang , Xu Jinfeng , Dong Fajin 
Published: June 2022

ObjectivesTo assess the feasibility and performance of Turbulence (Tur) index as a quantitative tool for carotid artery flow turbulence; to detect and compare the blood flow patterns of common carotid artery (CCA) and carotid bulb (CB) at different ages and cardiac phases in healthy adults, and thus interpret the evolvement of etiology difference between CCA and CB.MethodsCarotid flow characteristics of 40 healthy volunteers were evaluated quantitatively by a high‐frame rate vector flow imaging. Three types of flow patterns were defined depending on the distributive range of complex flow during systole in CB. Comparison of mean Tur value in CCA and CB at different age groups and cardiac phases was performed. And the correlation between Tur value and the diameter ratio of proximal internal carotid artery to common carotid artery (DRpro‐ica/cca) was tested.ResultsMean Tur values in CB were remarkably higher than that in CCA, whether during systole or diastole (P < .001). Meanwhile Tur values in CB during systole were significantly higher than that during diastole (P < .001). Flow complexity of CB showed variations among 40 participants especially in systole, whereas the flow pattern of CCA was relatively consistent. Mean Tur values were positively correlated with DRpro‐ica/cca in CB (ρ = 0.69, P < .05).ConclusionsV Flow imaging provided a reliable method—Tur, for quantitative analysis of carotid blood flow. It had potential to be further applied in distinguishing complex hemodynamic characteristics in high‐risk people of carotid diseases for the risk stratification of cardiovascular events.
Risk Stratification of Acute Invasive Fungal Rhinosinusitis in Patients With Hematologic Pathology
Authors: Navuluri Sriram , Gardner James Reed , Vickers Donald , Mohler Samantha , King Deanne , Kanaan Alissa 
Published: June 2022

ObjectiveThe purpose of this study is to identify objective perioperative diagnostic factors for acute invasive fungal rhinosinusitis (AIFS) to create a diagnostic scoring system using objective criteria.MethodsRetrospective case–control study performed at an academic, tertiary care center. Biopsy‐proven cases of AIFS identified from pathology records (2015–2019) were compared to patients the otolaryngology service was consulted to “Rule out AIFS” in the year 2019, only including those with underlying hematologic malignancy. Eighteen patients with AIFS and 20 patients without were included. One and two tailed T‐tests were used for p‐values. Receiver operating characteristic curves were generated for the significant data, and Youden's J‐statistic was used to create the ideal cutoff values for each. Likelihood ratios were used to give a power for the scoring system.ResultsCompared to patients with non‐hematologic malignancy‐related AIFS, patients with hematologic malignancy‐related AIFS have significantly elevated C‐reactive protein (CRP) and blood glucose; while albumin, hematocrit, platelet count, and absolute neutrophil count (ANC) were found to be significantly lower. In addition, Lund‐Mackay score asymmetry, extra‐sinus spread, aspergillus antigen, and pre‐existing diabetes mellitus correlated with disease. A scoring system with three categories: AIFS Unlikely, Indeterminate/AIFS Suspicious, and AIFS Highly Likely was developed.ConclusionPatients with hematologic malignancy‐related AIFS have measurable differences in lab values and standard imaging that could be used in determining the diagnostic probability of AIFS including: CRP, albumin, hematocrit, platelets, ANC, blood glucose, aspergillus antigen, Lund‐Mackay score asymmetry, extra‐sinus spread, and pre‐existing diabetes mellitus. A novel scoring system was proposed that will require prospective validation.Level of Evidence3 Laryngoscope, 133:1059–1064, 2023
Prognostic Utility of Tumor Stage versus American Thyroid Association Risk Class in Thyroid Cancer
Authors: Abiri Arash , Pang Jonathan , Prasad Karthik R. , Goshtasbi Khodayar , Kuan Edward C. , Armstrong William B. , Haidar Yarah M. , Tjoa Tjoson 
Published: June 2022

ObjectiveTo evaluate the prognostic strengths of American Joint Committee on Cancer (AJCC) staging and American Thyroid Association (ATA) risk classification in well‐differentiated thyroid cancer (DTC), and their implications in guiding medical decision‐making and epidemiological study designs.MethodsThe 2004–2017 National Cancer Database was queried for DTC patients. Cox proportional hazards (CPH) and Kaplan–Meier analyses modeled patient mortality and overall survival, respectively. Each CPH model was evaluated by its concordance index, measure of explained randomness (MER), Akaike information criterion (AIC), and area under receiver operating characteristic curve (AUC).ResultsOverall, 134,226 patients were analyzed, with an average age of 48.1 ± 15.1 years (76.9% female). Univariate CPH models using AJCC staging demonstrated higher concordance indices, MERs, and AUCs than those using ATA risk classification (all p < 0.001). Multivariable CPH models using AJCC staging demonstrated higher concordance indices (p = 0.049), MERs (p = 0.046), and AUCs (p = 0.002) than those using ATA risk classification. The AICs of multivariable AJCC staging and ATA risk models were 7.564 × 104 and 7.603 × 104, respectively. AJCC stage I tumors were associated with greater overall survival than those classified as ATA low risk, whereas AJCC stages II‐III and stage IV tumors demonstrated worse survival than ATA intermediate‐ and high‐risk tumors, respectively (all p < 0.001).ConclusionAJCC staging may be a more predictive system for patient survival than ATA risk. The prognostic utility of these two systems converges when additional demographic and clinical factors are considered. AJCC staging was found to classify patients across a wider range of survival patterns than the ATA risk stratification system.Level of Evidence4 Laryngoscope, 133:205–211, 2023