bluuebunny/crossref_metadata_2025_split huggingface dataset:
Th17, rather than Th1 cell proportion, is closely correlated with elevated disease severity, higher inflammation level, and worse prognosis in sepsis patients
Authors: Liu Yu , Wang Xiaopin , Yu Li 
Published: March 2021

AbstractObjectiveThe current study aimed to investigate the prognostic value of T helper (Th) 1 and Th17 proportions in sepsis patients.MethodsTh1 and Th17 cells in blood CD4+ T cells were detected by flow cytometry in 210 sepsis patients and 100 healthy controls (HCs). Besides, serum interferon‐γ (IFN‐γ), tumor necrosis factor‐α (TNF‐α), and interleukin‐17 (IL‐17) levels in the enrolled sepsis patients were determined with enzyme‐linked immunosorbent assay.ResultsCompared with HCs, Th1 and Th17 proportions were elevated in sepsis patients (both p < .001). Meanwhile, Th1 proportion was strongly correlated with IFN‐γ (p < .001, r = .484) but weakly correlated with TNF‐α (p = .024, r = .156) and IL‐17 (p = .002, r = .212), while Th17 proportion showed faint correlation with IFN‐γ (p = .015, r = .168), but strong correlations with TNF‐α (p < .001, r = .602) and IL‐17 (p < .001, r = .498) in sepsis patients. Besides, Th1 proportion was weakly associated with APACHE II score (p = .030, r = .150), but Th17 proportion was closely associated with APACHE II score (p < .001, r = .322) and SOFA score (p < .001, r = .337) in sepsis patients. Regarding their prognostic value, Th1 proportion (p = .042) was slightly, while Th17 proportion (p < .001) was dramatically, increased in septic deaths compared with survivors, and Th17 possessed good predictive value for 28‐day mortality risk (AUC: 0.748, 95% CI: 0.659–0.836).ConclusionTh1 and Th17 proportions are elevated in sepsis patients compared with HCs, and Th17 proportion is correlated with increased disease severity, higher inflammation level, and worse prognosis in sepsis patients.
Pseudo‐Enhancement in Intracranial Aneurysms on Black‐Blood MRI: Effects of Flow Rate, Spatial Resolution, and Additional Flow Suppression
Authors: Pravdivtseva Mariya S. , Gaidzik Franziska , Berg Philipp , Hoffman Carson , Rivera‐Rivera Leonardo A. , Medero Rafael , Bodart Lindsay , Roldan‐Alzate Alejandro , Speidel Michael A. , Johnson Kevin M. , Wieben Oliver , Jansen Olav , Hövener Jan‐Bernd , Larsen Naomi 
Published: March 2021

BackgroundVessel‐wall enhancement (VWE) on black‐blood MRI (BB MRI) has been proposed as an imaging marker for a higher risk of rupture and associated with wall inflammation. Whether VWE is causally linked to inflammation or rather induced by flow phenomena has been a subject of debate.PurposeTo study the effects of slow flow, spatial resolution, and motion‐sensitized driven equilibrium (MSDE) preparation on signal intensities in BB MRI of patient‐specific aneurysm flow models.Study TypeProspective.Subjects/Flow Aneurysm Model/Virtual VesselsAneurysm flow models based on 3D rotational angiography datasets of three patients with intracranial aneurysms were 3D printed and perfused at two different flow rates, with and without Gd‐containing contrast agent.Field Strength/SequenceVariable refocusing flip angle 3D fast‐spin echo sequence at 3 T with and without MSDE with three voxel sizes ((0.5 mm)3, (0.7 mm)3, and (0.9 mm)3); time‐resolved with phase‐contrast velocity‐encoding 3D spoiled gradient echo sequence (4D flow MRI).AssessmentThree independent observers performed a qualitative visual assessment of flow patterns and signal enhancement. Quantitative analysis included voxel‐wise evaluation of signal intensities and magnitude velocity distributions in the aneurysm.Statistical TestsKruskal–Wallis test, potential regressions.ResultsA hyperintense signal in the lumen and adjacent to the aneurysm walls on BB MRI was colocalized with slow flow. Signal intensities increased by a factor of 2.56 ± 0.68 (P < 0.01) after administering Gd contrast. After Gd contrast administration, the signal was suppressed most in conjunction with high flows and with MSDE (2.41 ± 2.07 for slow flow without MSDE, and 0.87 ± 0.99 for high flow with MSDE). A clear result was not achieved by modifying the spatial resolution .Data ConclusionsSlow‐flow phenomena contribute substantially to aneurysm enhancement and vary with MRI parameters. This should be considered in the clinical setting when assessing VWE in patients with an unruptured aneurysm.Evidence Level2Technical EfficacyStage 2
Deep Learning for Automatic Differential Diagnosis of Primary Central Nervous System Lymphoma and Glioblastoma: Multi‐Parametric Magnetic Resonance Imaging Based Convolutional Neural Network Model
Authors: Xia Wei , Hu Bin , Li Haiqing , Shi Wei , Tang Ying , Yu Yang , Geng Chen , Wu Qiuwen , Yang Liqin , Yu Zekuan , Geng Daoying , Li Yuxin 
Published: March 2021

BackgroundDifferential diagnosis of primary central nervous system lymphoma (PCNSL) and glioblastoma (GBM) is useful to guide treatment strategies.PurposeTo investigate the use of a convolutional neural network (CNN) model for differentiation of PCNSL and GBM without tumor delineation.Study TypeRetrospective.PopulationA total of 289 patients with PCNSL (136) or GBM (153) were included, the average age of the cohort was 54 years, and there were 173 men and 116 women.Field Strength/Sequence3.0 T Axial contrast‐enhanced T1‐weighted spin‐echo inversion recovery sequence (CE‐T1WI), T2‐weighted fluid‐attenuation inversion recovery sequence (FLAIR), and diffusion weighted imaging (DWI, b = 0 second/mm2, 1000 seconds/mm2).AssessmentA single‐parametric CNN model was built using CE‐T1WI, FLAIR, and the apparent diffusion coefficient (ADC) map derived from DWI, respectively. A decision‐level fusion based multi‐parametric CNN model (DF‐CNN) was built by combining the predictions of single‐parametric CNN models through logistic regression. An image‐level fusion based multi‐parametric CNN model (IF‐CNN) was built using the integrated multi‐parametric MR images. The radiomics models were developed. The diagnoses by three radiologists with 6 years (junior radiologist Y.Y.), 11 years (intermediate‐level radiologist Y.T.), and 21 years (senior radiologist Y.L.) of experience were obtained.Statistical AnalysisThe 5‐fold cross validation was used for model evaluation. The Pearson's chi‐squared test was used to compare the accuracies. U‐test and Fisher's exact test were used to compare clinical characteristics.ResultsThe CE‐T1WI, FLAIR, and ADC based single‐parametric CNN model had accuracy of 0.884, 0.782, and 0.700, respectively. The DF‐CNN model had an accuracy of 0.899 which was higher than the IF‐CNN model (0.830, P = 0.021), but had no significant difference in accuracy compared to the radiomics model (0.865, P = 0.255), and the senior radiologist (0.906, P = 0.886).Data ConclusionA CNN model can differentiate PCNSL from GBM without tumor delineation, and comparable to the radiomics models and radiologists.Level of Evidence4Technical EfficacyStage 2
Use of ion mobility‐high resolution mass spectrometry in metabolomics studies to provide near MS/MS quality data in a single injection
Authors: Gil‐Solsona Rubén , Sancho Juan V. , Gassner Anne‐Laure , Weyermann Céline , Hernández Félix , Delémont Olivier , Bijlsma Lubertus 
Published: March 2021

AbstractThe use of ion mobility separations (IMSs) in metabolomics approaches has started to be deeply explored in the last years. In this work, the use of liquid chromatography (LC) coupled to IMS‐quadrupole time‐of‐flight mass spectrometry (QTOF MS) has been evaluated in a metabolomics experiments using single injection of the samples. IMS has allowed obtaining cleaner fragmentation spectra, of nearly tandem MS quality, in data‐independent acquisition mode. This is much useful in this research area as a second injection, generally applied in LC‐QTOF MS workflows to obtain tandem mass spectra, is not necessary, saving time and evading possible compound degradation. As a case study, the smoke produced after combustion of herbal blends used to spray synthetic cannabinoids has been selected as study matrix. The smoke components were trapped in carbon cartridges, desorbed and analyzed by LC‐IMS‐QTOF MS using different separation mechanisms (reversed phase and HILIC) and acquiring in both positive and negative mode to widen the chemical domain. Partial Least Squares–Discriminant Analysis highlighted several compounds, and ratio between N‐Isopropyl‐3‐(isoquinolinyl)‐2‐propen‐1‐amine and quinoline allowed differentiating between tobacco and herbal products. These two compounds were tentatively identified using the cleaner fragmentation spectra from a single injection in the IMS‐QTOF MS, with additional confidence obtained by retention time (Rt) and collisional cross section (CCS) prediction using artificial neural networks. Data from this work show that LC‐IMS‐QTOF is an efficient technique in untargeted metabolomics, avoiding re‐injection of the samples for elucidation purposes. In addition, the prediction models for Rt and CCS resulted of help in the elucidation process of potential biomarkers.
Characterization of subsurface cracks in eddy current testing using machine learning methods
Authors: Barrarat Fatima , Rayane Karim , Helifa Bachir , Lefkaier Ibn Khaldoun 
Published: March 2021

AbstractThe exploitation of nondestructive eddy current testing (NDT‐EC) has become a capital necessity. Therefore, the development of a fast tool for the eddy‐current signal inversion is necessary. This paper proposes an inversion of signals coming from the NDT‐EC sensor response using machine learning methods, to reconstruct the length and depth of the defect and obtain its geometric characterization by solving the inverse problem. In this context, a database comprising the impedance of the sensor‐cracked part system (constituting the crack signature) was constructed from a 3D finite element simulation and validated by an experimental companion. The machine learning algorithms were trained using this database. The results show that the defect can be quantified using these developed approaches. The numerical approach can replace the expensive experimental investigation or the optimization algorithm that has a prohibitive computing time. The results show that the approaches developed estimated the desired parameters of the crack with good precision. These different machine learning methods for solving the inverse problem were implemented using the MATLAB software.
Energy expenditure and oxygen uptake kinetics in critically ill elderly patients
Authors: Ebihara Takeshi , Shimizu Kentaro , Ojima Masahiro , Nakamura Yohei , Mitsuyama Yumi , Ohnishi Mitsuo , Ogura Hiroshi , Shimazu Takeshi 
Published: March 2021

AbstractBackgroundResting energy expenditure (REE) measurement of critically ill patients is essential for better nutrition management. Younger people increase their oxygen delivery () to meet energy demands, but few reports have investigated oxygen uptake kinetics in elderly patients, which are the main target population in today's intensive care units (ICUs). In this study, we evaluated REE, , and oxygen extraction ratio (O2 Ext: oxygen consumption []/) to clarify appropriate energy needs and consumption in elderly ICU patients.MethodsThis retrospective observational study included ventilated ICU patients who were divided into elderly participants (age ≥ 65 years) and nonelderly participants (age ≤64 years). , CO2 production, and cardiac output were measured by indirect calorimetry and noninvasive hemodynamic monitoring for up to 5 days. The initial values of REE, , and O2 Ext were compared between elderly and nonelderly patients.ResultsThis study included 102 patients, of whom 52% (n = 53) were elderly. The absolute deviation of measured REE per ideal body weight (IBW) was significantly higher in elderly than in nonelderly patients (9.3 ± 6.9 vs 6.3 ± 6.6 kcal/kg; P < .01). had a strong negative correlation with age (P < .01). The O2 Ext value was significantly higher in elderly than in nonelderly patients (37 ± 19% vs 29 ± 13%; P = .03).ConclusionsElderly critically ill patients were characterized by higher deviations in REE, lower , and higher O2 Ext. In elderly patients, O2 Ext rather than could be increased to meet energy consumption demands.
Environmental perceptions and willingness to pay for preservation: Evidence from beach destinations in China
Authors: Liu Jia , Zhao Yichen , Jang Soo Cheong(Shawn) 
Published: March 2021

AbstractBeaches are regarded as a core resource in coastal tourism. However, they are being eroded by environmental pollution, which has negative impacts on visitors' tourism experiences. This study proposed a framework to elaborate the effects of visitors' environmental perceptions on satisfaction and willingness to pay for environmental protection. The findings revealed that visitors' perceptions of a beach's quality had significant positive effects on their satisfaction. Furthermore, satisfaction significantly increased visitors' willingness to pay for environmental protection. In addition, visitors' perceptions of the beach environment had a direct and positive impact on their willingness to pay for environmental protection.
Cardiopulmonary Testing before Pediatric Adenotonsillectomy for Severe and Very Severe Obstructive Sleep Apnea Syndrome
Authors: Clements Anna Christina , Walsh Jonathan M. , Dai Xi , Skinner Margaret L. , Sterni Laura M. , Tunkel David E. , Boss Emily F. , Ryan Marisa A. 
Published: March 2021

Objectives/HypothesisAdenotonsillectomy is first‐line treatment for pediatric obstructive sleep apnea syndrome (OSAS) when not otherwise contraindicated. There is concern severe OSAS increases risk of comorbid cardiopulmonary abnormalities, such as ventricular hypertrophy or pulmonary hypertension, which preoperative testing could detect. Our objective is to determine if there is a severity of pediatric OSAS where previously undetected cardiopulmonary comorbidities are likely.Study DesignRetrospective chart review.MethodsWe performed a retrospective review of 358 patients ≤21 years with severe OSAS who underwent adenotonsillectomy at a tertiary hospital June 1, 2016 to June 1, 2018. We extracted demographics, comorbidities, polysomnography, and preoperative tests. Wilcoxon rank‐sum and logistic regression estimated associations of OSAS severity (based on obstructive apnea‐hypopnea index [OAHI], hypoxia, hypercarbia) with preoperative echocardiograms and chest X‐rays (CXRs).ResultsMean age was 5.9 (±3.6) years and 52% were male. Mean OAHI and oxygen saturation nadir were 30.3 (±23.8) and 80.7% (±9.2), respectively. OAHI ≥60 was associated with having a preoperative echocardiogram (OR, 3.8; 95% CI, 1.7–8.5) or CXR (OR, 3.0; 95% CI, 1.4–6.8) compared to OAHI 10–59. There were no significant associations between OSAS severity and test abnormalities. The presence of previously diagnosed cardiopulmonary comorbidities was associated with abnormalities on echocardiogram (OR, 36; 95% CI, 4.1–320.1) and CXR (OR, 4.1; 95% CI, 1.2–14.4).ConclusionsAlthough pediatric patients with very severe OSAS (OAHI ≥60) underwent more pre‐adenotonsillectomy cardiopulmonary tests, OSAS severity did not predict abnormal findings. Known cardiopulmonary comorbidities may be a better indication for cardiopulmonary testing than polysomnographic parameters, which could streamline pre‐adenotonsillectomy evaluation and reduce cost.Level of Evidence4Laryngoscope, 131:2361–2368, 2021
Digital anthropometric volumes: Toward the development and validation of a universal software
Authors: Sobhiyeh Sima , Dunkel Alexander , Dechenaud Marcelline , Mehrnezhad Ali , Kennedy Samantha , Shepherd John , Wolenski Peter , Heymsfield Steven B. 
Published: March 2021

PurposeAnthropometry is a method for quantifying body size and shape often used to derive body composition and health risk prediction models. Recent technology advancements led to development of three‐dimensional (3D) optical scanners that can overcome most of the limitations associated with manual anthropometric data collection. However, each of the currently available devices offers proprietary measurements that do not match conventional anthropometric definitions. The aim of the current study was to develop and then evaluate the precision and accuracy of new “universal” 3D optical analysis software that calculates digital anthropometric volumes using identical standard landmarks across scanners.MethodsDual‐energy x‐ray absorptiometry (DXA) and air displacement plethysmography (ADP) total body and regional volume and fat mass reference measurements and 3D optical scans from two proprietary devices were collected from 356 participants to evaluate the robustness of total body and regional volume and fat mass measurements calculated by the developed software. Linear regression modeling with threefold cross validation was used to evaluate total body and regional fat masses from 3D scans.ResultsTotal body and regional volumes measured by DXA and ADP had strong associations with corresponding estimates from the commercial 3D optical scanners coupled with the universal software (e.g., R2 = 0.98 for Styku and R2 = 1.00 for SS20, for both DXA and ADP comparisons). Regional body volumes also had strong correlation between DXA and the 3DO scanners (e.g., for arm, leg and trunk, respective R2s of 0.75, 0.86, and 0.97 for Styku and 0.79, 0.89, and 0.98 for SS20). Similarly, there were strong associations between DXA‐ measured total body and regional fat mass and 3D optical estimates calculated by the universal software (e.g., for total body, arm, leg and trunk, respective R2s of 0.86, 0.72, 0.77, and 0.88 for Styku and 0.84, 0.76, 0.78, and 0.85 for SS20). Absolute differences in volumes and fat mass between the reference methods and the universal software values revealed underlying proprietary scanner differences that can be improved when designing future devices.ConclusionsThe current study suggests that, when compared against values calculated using DXA and ADP, the universal software was able to measure total and regional body volumes reliably from scans obtained by two different scanners. The universal software, with future refinements, combined with potential optical scanner design improvements, creates new opportunities for developing large multicenter anthropometric databases with uniformly defined body dimensions that can be used for modeling health risks.Clinical Trial Registration IDShape Up! Adults Study, NCT0363785.
Randomized Controlled Trial of Treatments for Loss‐of‐Control Eating Following Bariatric Surgery
Authors: Grilo Carlos M. , Ivezaj Valentina , Duffy Andrew J. , Gueorguieva Ralitza 
Published: March 2021

ObjectiveLoss‐of‐control (LOC) eating postoperatively is a consistent predictor of suboptimal longer‐term bariatric surgery outcomes. This randomized controlled trial examined the effectiveness of two guided self‐help treatments (cognitive behavioral therapy [gshCBT] and behavioral weight loss [gshBWL]) compared with a control (CON) for reducing LOC eating and weight.MethodsA total of 140 patients with recurrent LOC eating approximately 6 months after bariatric surgery were randomly assigned (5:5:2 ratio) to one of three conditions: gshCBT (n  =  56), gshBWL (n  =  60), or CON (n  =  24). Three‐month treatments were delivered by trained allied health clinicians to increase generalizability to bariatric surgery settings. Independent assessments were performed by doctoral research‐clinicians using established interviews/measures; posttreatment outcomes were obtained for 89% of patients.ResultsMixed models revealed significant improvements for LOC eating frequency and weight loss but no significant differences between treatments; race neither predicted (main effect) nor moderated (interaction effect) treatment outcomes. Intent‐to‐treat categorical analyses of abstinence from LOC eating (30% for gshCBT, 27% for gshBWL, 38% for CON) and proportion attaining 5% weight loss (20%, 22%, 17%) revealed no significant differences between treatments; non‐White participants had a higher proportion achieving LOC eating abstinence but a lower proportion attaining 5% weight loss compared with White participants.ConclusionsIn this 12‐week randomized controlled trial following bariatric surgery, significant LOC eating reductions and weight loss did not differ significantly between treatments. Race was associated with posttreatment categorical outcomes.
Synthesis of aramid nanoscale fiber‐based nanocomposite with transparency, flexibility, and selective adsorption capability
Authors: Wu Yadong , Ju Dandan , Wang Fang , Huang Yudong 
Published: March 2021

AbstractAramid nanofiber (ANF) has been regarded as an emerging excellent building block for preparing multifunctional high‐performance composites, which are suitable for many applications in various fields. Based on this, for the first time, nanoscale bacterial cellulose (NBC) is used to modify ANF membrane via a direct blending followed with vacuum filtration. The chemical and physical structures of the NBC/ANF composite hybrid membranes (BAFM) are characterized by using Fourier transform infrared, X‐ray diffraction, transmission electron microscope, and scanning electron microscope, demonstrating that NBC is well‐dispersed into the ANF matrix. The two kinds of nanofibers twine together and interact with each other through hydrogen bonds, so that the tensile strength is enhanced from approximately 202–260 MPa by the incorporation of NBC. Besides, it is notable that the transparency retains due to the nanoscale diameter (much smaller than light wavelength) of the nanofibers, and the flexibility of the membranes is improved. Furthermore, the measurement of wettability shows that the hydrophilicity of the composite membranes could be improved by the addition of NBC, and the static water contact angle decreases from 85.6° to 63.5°. The adsorption process toward cationic (methylene blue, MB) and anionic (methyl orange, MO) dyes are preliminarily investigated, respectively. Due to the negatively charged ANF and the hydrophilic NBC, the BAFM exhibits selective adsorption ability toward MB, and the capacity could be improved by increasing the amount of NBC. Therefore, NBC is a desirable modifier for ANF to fabricate the composite, which is a promising candidate for transparent, flexible membranes with selective adsorption capacity.