bluuebunny/crossref_metadata_2025_split huggingface dataset:
DNA methylation fingerprint of hepatocellular carcinoma from tissue and liquid biopsies
Authors: Gonçalves Emanuel , Gonçalves-Reis Maria , Pereira-Leal José B. , Cardoso Joana 
Published: July 2022

AbstractHepatocellular carcinoma (HCC) is amongst the cancers with highest mortality rates and is the most common malignancy of the liver. Early detection is vital to provide the best treatment possible and liquid biopsies combined with analysis of circulating tumour DNA methylation show great promise as a non-invasive approach for early cancer diagnosis and monitoring with low false negative rates. To identify reliable diagnostic biomarkers of early HCC, we performed a systematic analysis of multiple hepatocellular studies and datasets comprising > 1500 genome-wide DNA methylation arrays, to define a methylation signature predictive of HCC in both tissue and cell-free DNA liquid biopsy samples. Our machine learning pipeline identified differentially methylated regions in HCC, some associated with transcriptional repression of genes related with cancer progression, that benchmarked positively against independent methylation signatures. Combining our signature of 38 DNA methylation regions, we derived a HCC detection score which confirmed the utility of our approach by identifying in an independent dataset 96% of HCC tissue samples with a precision of 98%, and most importantly successfully separated cfDNA of tumour samples from healthy controls. Notably, our risk score could identify cell-free DNA samples from patients with other tumours, including colorectal cancer. Taken together, we propose a comprehensive HCC DNA methylation fingerprint and an associated risk score for detection of HCC from tissue and liquid biopsies.
Photo-supercapacitors based on nanoscaled ZnO
Authors: Altaf Cigdem Tuc , Coskun Ozlem , Kumtepe Alihan , Rostas Arpad Mihai , Iatsunskyi Igor , Coy Emerson , Erdem Emre , Sankir Mehmet , Sankir Nurdan Demirci 
Published: July 2022

AbstractIn this study, zinc oxide (ZnO) powders in two different morphologies, nanowire (NW) and nanoflower (NF), have been synthesized by the hydrothermal method. The eligibility of the pristine ZnO nanopowders as a photo-active material has been revealed by designing P-SC devices via the facile drop-casting method on both glass and plastic substrates in large-area applications. The impact of physical properties and especially defect structures on photo-supercapacitor (P-SC) performance have been explored. Although the dark Coulombic efficiency (CE%) of both NW and NF-based P-SC were very close to each other, the CE% of NW P-SC increased 3 times, while the CE% of NF P-SC increased 1.7 times under the UV-light. This is because the charge carriers produced under light excitation, extend the discharge time, and as confirmed by electron paramagnetic resonance, photoluminescence, and transmission electron microscopy analyses, the performance of P-SCs made from NF powders was relatively low compared to those produced from NW due to the high core defects in NF powders. The energy density of 78.1 mWh kg−1 obtained for NF-based P-SCs is very promising, and the capacitance retention value of almost 100% for 3000 cycles showed that the P-SCs produced from these materials were entirely stable. Compared to the literature, the P-SCs we propose in this study are essential for new generation energy storage systems, thanks to their ease of design, adaptability to mass production for large-area applications, and their ability to store more energy under illumination.
Application of Extremely Randomised Trees for exploring influential factors on variant crash severity data
Authors: Afshar Farshid , Seyedabrishami Seyedehsan , Moridpour Sara 
Published: July 2022

AbstractCrash severity models play a crucial role in evaluating the influencing factors in the severity of traffic crashes. In this study, Extremely Randomised Tree (ERT) is used as a machine learning technique to analyse the severity of crashes. The crash data in the province of Khorasan Razavi, Iran, for a period of 5 years from 2013 to 2017, is used for crash severity model development. The dataset includes traffic-related variables, vehicle specifications, vehicle movement, land use characteristics, temporal characteristics, and environmental variables. In this paper, Feature Importance Analysis (FIA), Partial Dependence Plots (PDP), and Individual Conditional Expectation (ICE) plots are utilised to analyse and interpret the results. According to the results, the involvement of vulnerable road users such as motorcyclists and pedestrians alongside traffic-related variables are among the most significant variables in crash severity. Results show that the presence of motorcycles can increase the probability of injury crashes by around 30% and almost double the probability of fatal crashes. Analysing the interaction of PDPs shows that driving speeds above 60 km/h in residential areas raises the probability of injury crashes by about 10%. In addition, at speeds higher than 70 km/h, the presence of pedestrians approximately increases the probability of fatal crashes by 6%.
Identification of Guiboutia species by NIR-HSI spectroscopy
Authors: Xue Xiaoming , Chen Zhenan , Wu Haoqi , Gao Handong 
Published: July 2022

AbstractNear infrared hyperspectral imaging (NIR-HSI) spectroscopy can be a rapid, precise, low-cost and non-destructive way for wood identification. In this study, samples of five Guiboutia species were analyzed by means of NIR-HSI. Partial least squares discriminant analysis (PLS-DA) and support vector machine (SVM) were used after different data treatment in order to improve the performance of models. Transverse, radial, and tangential section were analyzed separately to select the best sample section for wood identification. The results obtained demonstrated that NIR-HSI combined with successive projections algorithm (SPA) and SVM can achieve high prediction accuracy and low computing cost. Pre-processing methods of SNV and Normalize can increase the prediction accuracy slightly, however, high modelling accuracy can still be achieved by raw pre-processing. Both models for the classification of G. conjugate, G. ehie and G. demeusei perform nearly 100% accuracy. Prediction for G. coleosperma and G. tessmannii were more difficult when using PLS-DA model. It is evidently clear from the findings that the transverse section of wood is more suitable for wood identification. NIR-HSI spectroscopy technique has great potential for Guiboutia species analysis.
Melting enhancement of PCM in a finned tube latent heat thermal energy storage
Authors: Ahmed Sameh , Abderrahmane Aissa , Saeed Abdulkafi Mohammed , Guedri Kamel , Mourad Abed , Younis Obai , Botmart Thongchai , Shah Nehad Ali 
Published: July 2022

AbstractThe current paper discusses the numerical simulation results of the NePCM melting process inside an annulus thermal storage system. The TES system consists of a wavy shell wall and a cylindrical tube equipped with three fins. The enthalpy-porosity method was utilized to address the transient behavior of the melting process, while the Galerkin FE technique was used to solve the system governing equations. The results were displayed for different inner tube positions (right-left–up and down), inner cylinder rotation angle (0 ≤ α ≤ 3π/2), and the nano-additives concentration (0 ≤ ϕ ≤ 0.04). The findings indicated that high values of nano-additives concentration (0.4), bigger values of tube rotation angle (3π/2), and location of the tube at the lower position accelerated the NePCM melting process.
NK cell spatial dynamics and IgA responses in gut-associated lymphoid tissues during SIV infections
Authors: Rascle Philippe , Planchais Cyril , Jacquelin Béatrice , Lazzerini Marie , Contreras Vanessa , Passaes Caroline , Saez-Cirion Asier , Mouquet Hugo , Huot Nicolas , Müller-Trutwin Michaela 
Published: July 2022

AbstractHIV infection induces tissue damage including lymph node (LN) fibrosis and intestinal epithelial barrier disruption leading to bacterial translocation and systemic inflammation. Natural hosts of SIV, such as African Green Monkeys (AGM), do not display tissue damage despite high viral load in blood and intestinal mucosa. AGM mount a NK cell-mediated control of SIVagm replication in peripheral LN. We analyzed if NK cells also control SIVagm in mesenteric (mes) LN and if this has an impact on gut humoral responses and the production of IgA known for their anti-inflammatory role in the gut. We show that CXCR5 + NK cell frequencies increase in mesLN upon SIVagm infection and that NK cells migrate into and control viral replication in B cell follicles (BCF) of mesLN. The proportion of IgA+ memory B cells were increased in mesLN during SIVagm infection in contrast to SIVmac infection. Total IgA levels in gut remained normal during SIVagm infection, while strongly decreased in intestine of chronically SIVmac-infected macaques. Our data suggest an indirect impact of NK cell-mediated viral control in mesLN during SIVagm infection on preserved BCF function and IgA production in intestinal tissues.
Single-cell stable isotope probing in microbial ecology
Authors: Alcolombri Uria , Pioli Roberto , Stocker Roman , Berry David 
Published: July 2022

Abstract
Environmental and host-associated microbiomes are typically diverse assemblages of organisms performing myriad activities and engaging in a network of interactions that play out in spatially structured contexts. As the sum of these activities and interactions give rise to overall microbiome function, with important consequences for environmental processes and human health, elucidating specific microbial activities within complex communities is a pressing challenge. Single-cell stable isotope probing (SC-SIP) encompasses multiple techniques that typically utilize Raman microspectroscopy or nanoscale secondary ion mass spectrometry (NanoSIMS) to enable spatially resolved tracking of isotope tracers in cells, cellular components, and metabolites. SC-SIP techniques are uniquely suited for illuminating single-cell activities in microbial communities and for testing hypotheses about cellular functions generated for example from meta-omics datasets. Here, we illustrate the insights enabled by SC-SIP techniques by reviewing selected applications in microbiology and offer a perspective on their potential for future research.
Double hyperbolic sliding mode control of a three‐legged robot with actuator constraints
Authors: Ghoreishi Seyyed Alireza , Ehyaei Amir Farhad , Rahmani Mehdi 
Published: July 2022

AbstractThis paper proposes an anti‐wind up double hyperbolic sliding mode controller (AWDH‐SMC) in the presence of torque constraints for a three‐legged robot. The legged robot's dynamics are nonlinear, hybrid and complex. Based on the challenges mentioned, this study focuses on designing a sliding mode controller (SMC) for a fully actuated three‐legged robot to achieve fast tracking and convergence. On the other hand, the torques generated by the actuators are limited. As a result, not only must the controller be fast so that the robot's balance is not disturbed, but it must also withstand applied torque constraints. Therefore, the double hyperbolic sliding mode controller is designed at first for fast tracking and convergence. Next, an anti‐wind up compensator is used to apply torque constraints. Finally, using the theory of multiple Lyapunov functions, the stability of the closed‐loop control system for the hybrid model of legged‐robot is analyzed. Simulation results validate the effectiveness of the proposed control scheme.
Efficient pavement distress classification via deep patch soft selective learning and knowledge distillation
Authors: Zhang Shizheng , Tang Wenhao , Wang Jing , Huang Sheng 
Published: July 2022

AbstractPavement distress classification is a vital step for automatic pavement inspection and maintenance. Recently, patch‐based approaches have achieved promising performances and thus extensive attention in this field. However, these methods simply assume that all patches contribute equally to the distress classification, leading to weakly discriminating abilities of models. Moreover, their tedious processes also lead to low efficiency in inference. The authors present a novel patch‐based pavement distress classification approach named Deep Patch Soft Selective Learning, which addresses these issues. Similar to other patch‐based approaches, Deep Patch Soft Selective Learning partitions the pavement images into patches and aggregates the patch features to accomplish the task. To address the first issue, a succinct Soft Patch Feature Selection Network is introduced to assess the importance of each patch to the distress classification with a score based on its feature. These scores will be considered as patch‐wise weights for feature aggregation. In such a manner, the most discriminative patches are selected in a soft way, and thereby benefit the final classification. To address the inference efficiency issue, knowledge distillation is leveraged to transfer the classification knowledge from Deep Patch Soft Selective Learning to the image‐based approaches, such as EfficientNet‐B3. This distilled model enables incorporating both the advantages of patch‐based approaches in classification performance and the advantages of image‐based approaches in inference efficiency. Extensive experiments on a large‐scale pavement image dataset named CQU‐BPDD demonstrate that Deep Patch Soft Selective Learning outperforms the baselines by a large margin of +7.4% in P@R on the detection task and +3.1% in F1 on the recognition task while enjoying 2.1x throughput of baselines.
A survey on methods, datasets and implementations for scene text spotting
Authors: Blanco‐Medina Pablo , Fidalgo Eduardo , Alegre Enrique , González‐Castro Víctor 
Published: July 2022

AbstractText Spotting is the union of the tasks of detection and transcription of the text that is present in images. Due to the various problems often found when retrieving text, such as orientation, aspect ratio, vertical text or multiple languages in the same image, this can be a challenging task. In this paper, the most recent methods and publications in this field are analysed and compared. Apart from presenting features already seen in other surveys, such as their architectures and performance on different datasets, novel perspectives for comparison are also included, such as the hardware, software, backbone architectures, main problems to solve, or programming languages of the algorithms. The review highlights information often omitted in other studies, providing a better understanding of the current state of research in Text Spotting, from 2016 to 2022, current problems and future trends, as well as establishing a baseline for future methods development, comparison of results and serving as guideline for choosing the most appropriate method to solve a particular problem.
Müde Mitochondrien
Authors: Feldhaus Simon 
Published: July 2022

SummaryAnhand des vorliegenden Fallbeispiels veranschaulicht der Autor, wie bestimmte Virusinfektionen ein – häufig fehldiagnostiziertes postvirales Fatigue-Syndrom nach sich ziehen können. Zu den Kardinalsymptomen gehören körperliche und geistige Erschöpfung und gesteigerte Ermüdbarkeit, begleitet von unter anderem Muskelschmerzen, Gedächtnis- sowie anderen kognitiven Störungen. Eine häufige Ursache ist eine Mitochondriopathie. Sie kann nach einer Funktionstestung der Mitochondrien individuell und kausal mit orthomolekularer Medizin (OM) behandelt werden.
New Markers for Placental Dysfunction at Term – Potential for More
Authors: Graupner Oliver , Kuschel Bettina , Axt-Fliedner Roland , Enzensberger Christian 
Published: July 2022

AbstractThe remaining placental reserve capacity at term plays a decisive role in the perinatal morbidity of mother and child. Considering advances made in the field of fetal monitoring, the
routine examination methods currently used at term or late term may be insufficient to detect subclinical placental dysfunction (PD). The aim of this study is to offer an up-to-date,
narrative review of the literature in the context of detecting PD at term using complementary ultrasound markers and biomarkers. Parameters of fetomaternal Doppler ultrasound and fetal
cardiac function, as well as (anti-)angiogenic factors in maternal serum are potential PD markers. These may help identify patients that may benefit from an elective, early induction of
labor at term, thereby potentially reducing morbidity and mortality. However, their value in terms of the optimal date of delivery must first be determined in randomized controlled trials on
a large number of cases.
Is Conversion Total Knee Arthroplasty a Distinct Surgical Procedure? A Comparison to Primary and Revision Total Knee Arthroplasty
Authors: Chen Zhongming , Sax Oliver C. , Bains Sandeep S. , Hebditch Cameron S. , Nace James , Delanois Ronald E. 
Published: July 2022

AbstractConversion total knee arthroplasty (TKA) is suggested to incur similar complication rates to revision arthroplasties. However, current billing codes do not allow for the differentiation between this operation and primary TKAs. Therefore, the purpose of this study was to compare outcomes of these two surgeries, as well as revision TKAs. Specifically, we analyzed (1) medical complications, (2) surgical complications, and (3) revision rates at 90 days and 1 year. We queried a national, all-payer database to identify patients who underwent TKA without prior implants (n = 1,358,767), required conversion TKA (n = 15,378), and who underwent revision TKA (n = 33,966) between January 1, 2010, and April 30, 2020. Conversion TKA patients (prior implant removal) were identified using the Current Procedural Terminology (CPT) codes. Outcomes studied included 30-day readmission rates and 90-day, as well as 1-year, medical and surgical complications. Conversion TKAs had greater 30-day readmission rates and incidences of most of the complications studied when compared with primary TKAs. The majority of outcomes when comparing between primary, conversion, and revision TKAs were significantly different (p < 0.01). In contrast, conversion TKA complications were similar to revision TKA. Conversion TKAs have higher postoperative complications than primary TKAs and share more similarities with revision TKAs. Thus, the lack of billing codes differentiating conversion and primary TKAs creates a challenge for orthopaedic surgeons.
Do Patellar Tendon Repairs Have Better Outcomes than Quadriceps Tendon Repairs? A Prospective Cohort Analysis
Authors: Yalcin Sercan , McCoy Brett , Farrow Lutul D. , Johnson Carrie , Jones Morgan H. , Kolczun Michael , Leo Brian , Miniaci Anthony , Nickodem Robert , Parker Richard , Serna Alfred , Stearns Kim , Strnad Greg , Williams James , Yuxuan Jin , Spindler Kurt P. 
Published: July 2022

AbstractPatellar tendon (PT) and quadriceps tendon (QT) ruptures represent significant injuries and warrant surgical intervention in most patients. Outcome data are predominantly retrospective analyses with low sample sizes. There are also minimal data comparing QT and PT repairs and the variables impacting patient outcomes. The level of evidence of the study is level II (prognosis). From the prospective OME cohort, 189 PT or QT repairs were performed between February 2015 and October 2019. Of these, 178 were successfully enrolled (94.2%) with 1-year follow-up on 141 (79.2%). Baseline demographic data included age, sex, race, BMI, years of education, smoking status, and baseline VR-12 MCS score. Surgical and follow-up data included surgeon volume, fixation technique, baseline, and 1-year Knee Injury and Osteoarthritis Outcome Score-Pain (KOOS-Pain), Knee Injury and Osteoarthritis Outcome Score—Physical Function (KOOS-PS), and 1-year Patient Acceptable Symptom State (PASS) scores and complications. Multivariable regression analysis was utilized to identify prognosis and significant risk factors for outcomes—specifically, whether KOOS-Pain or KOOS-PS were different between QT versus PT repairs. There were 59 patients in the PT cohort and 82 patients in QT cohort. Baseline demographic data demonstrated that PT cohort was younger (45.1 vs. 59.5 years, p <0.001), included significantly fewer patients of White race (51.7 vs. 80.0%, p = 0.001), lesser number of years of education (13.9 vs. 15.2 years, p = 0.020), a higher percentage of “high” surgeon volume (72.9% vs. 43.9%, p = 0.001) and 25.4% of PT repairs had supplemental fixation (QT had zero, p <0.001). Multivariable analysis identified gender (female-worse, p = 0.001), years of education (higher-better, p = 0.02), and baseline KOOS-Pain score (higher-better, p <0.001) as the risk factors that significantly predicted KOOS-Pain score. The risk factors that significantly predicted KOOS-PS were gender (female worse, p = 0.033), race (non-White-worse, p <0.001), baseline VR-12 MCS score (higher-better, p <0.001), and baseline KOOS-PS score (higher better, p = 0.029). KOOS-Pain and KOOS-PS scores improved after both QT and PT repairs. Patient reported pain and function at 1 year were similar between PT and QT repairs after adjusting for known risk factors. Multivariable analysis identified female gender and low baseline KOOS scores as predictors for worse outcomes.
What Are the Drivers of Readmission for Serious Venous Thromboembolic Events after Primary Total Knee Arthroplasty? An Analysis of 862,915 Patients
Authors: Rhoads Colin , Emara Ahmed K. , Pumo Thomas , Pan Xuankang , Zhou Guangjin , Koroukian Siran , Krebs Viktor E. , Piuzzi Nicolas S. 
Published: July 2022

AbstractVenous thromboembolism (VTE) is a relatively common complication among patients undergoing primary total knee arthroplasty (TKA). This complication occurs in a spectrum of severity ranging from an incidental finding to serious readmission-requiring events. To date, the risk factors of serious VTE that require readmission have not been characterized. This study examines the patient and hospital characteristics associated with readmission for serious VTE after TKA. The National Readmission Database (NRD) from the Agency of Healthcare Research and Quality (AHRQ) was queried for patients who underwent primary TKA from January 2016-December 2018. The study population consisted of patients who were readmitted within 90 days following primary TKA with a primary diagnosis of VTE. Multivariable regression models were constructed to evaluate patient characteristics (age, sex, insurance, elective nature of procedure, hospital characteristics, discharge status, income, and comorbidities) associated with higher risk of developing readmission-requiring VTE. Readmission rates for VTE exhibited a higher incidence in patients older than 61 (compared with 40 and under), males (OR:1.08, 95%CI [1.03–1.14]), patients with nonelective procedures (OR:20.21, 95% CI [19.16–21.32]), patients at large hospitals(OR:1.17, 95% CI [1.09–1.25]), patients at private hospitals (OR:1.19, 95% CI [1.09–1.29]), and patients with non-home discharge statuses. Comorbidities of paralysis (OR:1.52, 95% CI [1.19–1.94]), neurological disorders (OR:1.12, 95% CI [1.02–1.23]), metastatic cancer (OR:1.48, 95% CI [1.01–2.17]), obesity (OR:1.11, 95% CI [1.06–1.17]), fluid and electrolyte imbalance (OR:1.28, 95% CI [1.18–1.38]), blood loss anemia (OR:1.29, 95% CI [1.02–1.64]), and iron deficiency anemia (OR:1.24, 95 % CI [1.15–1.33]) increased risk of VTE. Certain comorbidities requiring chronic anticoagulation were associated with lower risk of VTE. Insurance status and patient income did not exhibit any correlation with VTE incidence. Patient characteristics of male sex, age > 61, and baseline comorbidities (paralysis, neurological disorders, metastatic cancer, obesity, fluid and electrolyte imbalance, and blood loss/iron deficiency anemia) were at an increased risk of developing serious VTE. Patients without continued supervision at their discharge environment were at higher risk of developing serious VTE. Extra prophylaxis and special protocols may be warranted in these patients to prevent VTE complications.