bluuebunny/crossref_metadata_2025_split huggingface dataset:
Reliability of task‐evoked neural activation during face‐emotion paradigms: Effects of scanner and psychological processes
Authors: Haller Simone P. , Chen Gang , Kitt Elizabeth R. , Smith Ashley R. , Stoddard Joel , Abend Rany , Cardenas Sofia I. , Revzina Olga , Coppersmith Daniel , Leibenluft Ellen , Brotman Melissa A. , Pine Daniel S. , Pagliaccio David 
Published: February 2022

AbstractAssessing and improving test–retest reliability is critical to efforts to address concerns about replicability of task‐based functional magnetic resonance imaging. The current study uses two statistical approaches to examine how scanner and task‐related factors influence reliability of neural response to face‐emotion viewing. Forty healthy adult participants completed two face‐emotion paradigms at up to three scanning sessions across two scanners of the same build over approximately 2 months. We examined reliability across the main task contrasts using Bayesian linear mixed‐effects models performed voxel‐wise across the brain. We also used a novel Bayesian hierarchical model across a predefined whole‐brain parcellation scheme and subcortical anatomical regions. Scanner differences accounted for minimal variance in temporal signal‐to‐noise ratio and task contrast maps. Regions activated during task at the group level showed higher reliability relative to regions not activated significantly at the group level. Greater reliability was found for contrasts involving conditions with clearly distinct visual stimuli and associated cognitive demands (e.g., face vs. nonface discrimination) compared to conditions with more similar demands (e.g., angry vs. happy face discrimination). Voxel‐wise reliability estimates tended to be higher than those based on predefined anatomical regions. This work informs attempts to improve reliability in the context of task activation patterns and specific task contrasts. Our study provides a new method to estimate reliability across a large number of regions of interest and can inform researchers' selection of task conditions and analytic contrasts.
Deciphering complex groundwater age distributions and recharge processes in a tropical and fractured volcanic multi‐aquifer system
Authors: Sánchez‐Murillo Ricardo , Montero‐Rodríguez Irene , Corrales‐Salazar José , Esquivel‐Hernández Germain , Castro‐Chacón Laura , Rojas‐Jiménez Luis D. , Vargas‐Víquez José , Pérez‐Quezadas Juan , Gazel Esteban , Boll Jan 
Published: February 2022

AbstractGroundwater recharge in highly fractured volcanic aquifers in the humid tropics remains poorly understood. In this region, rapid demographic growth and unregulated land use change are resulting in extensive surface water pollution and a large dependency on groundwater extraction. Here we present a multi‐tracer approach including δ18Oδ2H, 3H/3He dating, and noble gases (NG) within the most prominent multi‐aquifer system of central Costa Rica, with the objective to assess dominant groundwater recharge mechanisms and age distributions. We sampled wells and large springs across an elevation gradient from 868 to 2421 m asl. Our results indicate relatively young apparent ages ranging from 0.0 ± 3.2 up to 43.5 ± 7.6 years within the unconfined aquifer system. Helium isotopes (R/Ra up to 5.4) indicate a dominant signal from the upper mantle and preclude 3H/3He dating in 50% of the samples. Potential recharge elevations (based on NG and δ18O) ranged from ~1350 to 2670 m asl. NG‐derived recharge temperatures ranged from 11.0°C to 19.4°C. Recharge estimates varied from 129 ± 78 to 1605 ± 196 mm/yr with a mean value of 642 ± 117 mm/yr, representing 20.1 ± 4.0% of the total mean annual rainfall as effective recharge. The shallow unconfined aquifer is characterized by young and rapidly infiltrating water, whereas the deeper aquifer units have relatively older water (>60 years). These results are intended to guide the delineation and mapping of critical recharge areas in mountain headwaters to enhance water security and sustainability in the most important headwater dependent systems of Costa Rica.
Detection of a pituitary macroadenoma with transcranial ultrasonography: Principles and potential clinical applications
Authors: Meini Simone , Andreini Roberto , Cozza Sabino 
Published: February 2022

AbstractTranscranial color‐coded duplex sonography (TCCS) allows to study intracranial vessels through the intact skull, but the visualization of normal and pathologic brain structures in adults is often suboptimal due to inadequate acoustic window. The full potential of TCCS for clinical practice remains unfulfilled. Here, we describe the ability of TCCS to detect a non‐functioning pituitary macroadenoma in a 58‐year‐old man affected by headache. The macroadenoma was visualized as a roundish, well‐defined mass, mildly hyperechogenic compared to the hypoechogenic mesencephalic brainstem but mainly hypoechogenic compared to the surrounding intracranial structures. Intracranial vessels represented useful landmarks. Using tissue harmonic imaging mode, the borders of the macroadenoma were visualized more clearly. Macroadenoma characteristics were confirmed by magnetic resonance imaging. Neurosonologists should be aware of the possibility to incidentally find, during routinary TCCS, pituitary macroadenomas or other brain tumors (as incidentalomas), worthy to be recognized and referred for further investigations.
Superior cluneal nerve entrapment syndrome: a common but often overlooked cause of low back pain
Authors: Mizumoto Junki 
Published: February 2022

AbstractAn 81‐year‐old woman complained of low back pain (LBP) on her regular check‐up. Physical examination revealed tenderness at the middle point of the posterior iliac crest and burning dysesthesias around the tenderness point, without any other neurological findings. An injection of local anesthetics diminished the pain. The diagnosis of superior cluneal nerve entrapment syndrome (SCNES) was made. SCNES is relatively common, as high as 14% in patients with LBP, but frequently overlooked. Primary care physicians should be aware of the typical findings of SCNES for correct diagnosis and treatment.
Synthesis and antimicrobial evaluation of novel tris‐thiadiazole derivatives
Authors: Kalantarian Seyyed Jafar , Kefayati Hassan , Montazeri Naser 
Published: February 2022

Abstract1,1′,1″‐(((1,3,5‐triazine‐2,4,6‐triyl)tris(oxy))tris(benzene‐4,1‐diyl))tris(ethan‐1‐one) 1 reacted with extra bromine to afford the corresponding 1,1′,1″‐(((1,3,5‐triazine‐2,4,6‐triyl)tris(oxy))tris(benzene‐4,1‐diyl))tris(2‐bromoethan‐1‐one) 2. Also, reaction of acetophenone derivatives 3 with 5‐amino‐1,3,4‐thiadiazole‐2‐thiol 4 give the 5‐((1‐arylethylidene)amino)‐1,3,4‐thiadiazole‐2‐thiol 5. Compounds 5a–h reacted with 2 in the presences of acetic acid to afford novel 1,1′,1″‐(((1,3,5‐triazine‐2,4,6‐triyl)tris(oxy))tris(benzene‐4,1‐diyl))tris(2‐((5‐((1‐arylethylidene)amino)‐1,3,4‐thiadiazol‐2‐yl)thio)ethan‐1‐one) derivatives 6a–h. Antimicrobial activities of the products were evaluated against five bacterial strains including Streptococcus pneumoniae, Staphylococcus aureus, Bacillus subtilis, Escherichia coli, and Serratia marcescens. The antimicrobial results indicated that products 6b, 6d, and 6h had excellent activities as compared to other synthesized products against a variety of bacterial strains. The compounds having Cl and NO2 substituents showed notable inhibition of bacterial growth almost near to Ciprofloxacin as standard.
Breast MRI Background Parenchymal Enhancement Categorization Using Deep Learning: Outperforming the Radiologist
Authors: Eskreis‐Winkler Sarah , Sutton Elizabeth J. , D'Alessio Donna , Gallagher Katherine , Saphier Nicole , Stember Joseph , Martinez Danny F. , Morris Elizabeth A. , Pinker Katja 
Published: February 2022

BackgroundBackground parenchymal enhancement (BPE) is assessed on breast MRI reports as mandated by the Breast Imaging Reporting and Data System (BI‐RADS) but is prone to inter and intrareader variation. Semiautomated and fully automated BPE assessment tools have been developed but none has surpassed radiologist BPE designations.PurposeTo develop a deep learning model for automated BPE classification and to compare its performance with current standard‐of‐care radiology report BPE designations.Study TypeRetrospective.PopulationConsecutive high‐risk patients (i.e. >20% lifetime risk of breast cancer) who underwent contrast‐enhanced screening breast MRI from October 2013 to January 2019. The study included 5224 breast MRIs, divided into 3998 training, 444 validation, and 782 testing exams. On radiology reports, 1286 exams were categorized as high BPE (i.e., marked or moderate) and 3938 as low BPE (i.e., mild or minimal).Field Strength/SequenceA 1.5 T or 3 T system; one precontrast and three postcontrast phases of fat‐saturated T1‐weighted dynamic contrast‐enhanced imaging.AssessmentBreast MRIs were used to develop two deep learning models (Slab artificial intelligence (AI); maximum intensity projection [MIP] AI) for BPE categorization using radiology report BPE labels. Models were tested on a heldout test sets using radiology report BPE and three‐reader averaged consensus as the reference standards.Statistical TestsModel performance was assessed using receiver operating characteristic curve analysis. Associations between high BPE and BI‐RADS assessments were evaluated using McNemar's chi‐square test (α* = 0.025).ResultsThe Slab AI model significantly outperformed the MIP AI model across the full test set (area under the curve of 0.84 vs. 0.79) using the radiology report reference standard. Using three‐reader consensus BPE labels reference standard, our AI model significantly outperformed radiology report BPE labels. Finally, the AI model was significantly more likely than the radiologist to assign “high BPE” to suspicious breast MRIs and significantly less likely than the radiologist to assign “high BPE” to negative breast MRIs.Data ConclusionFully automated BPE assessments for breast MRIs could be more accurate than BPE assessments from radiology reports.Level of Evidence4Technical Efficacy Stage3
Bivariate bias correction of the regional climate model ensemble over the Adriatic region
Authors: Sokol Jurković Renata , Güttler Ivan , Pasarić Zoran 
Published: February 2022

AbstractThe main goal of this analysis is to provide an assessment of the fine grid regional climate model (RCM) ensemble over the broader Adriatic region, which is the domain with orographically complex terrain and a developed coastline. The results of this study are a beneficial complement to earlier work on using modified bivariate bias correction methods. This analysis was based on an ensemble of 12 combinations of three RCMs and four global climate models (GCMs) from 1971 to 2004, divided into calibration and validation parts. A comparison of one univariate and three versions of bivariate bias correction methods of summer and winter monthly temperature and precipitation was performed. To examine the effect of various methods, we used different marginal distributions and distributions of dependence (copula). Bivariate bias correction was conducted with parametric and empirical marginal distributions. In the quantile mapping (univariate) and the parametric bivariate method, gamma (precipitation) and normal (temperature) probability distributions were used. We documented the bias and the influence of bias correction methods on precipitation and temperature, including their climate change signals in historical data. The considered methods maintained the spatial distribution of trends from the native ensemble. If the relationship between variables was not distinct and the correlation coefficient was low, bivariate bias correction methods tended to weaken the correlation coefficient from the model. Two experiments on how the bias correction methods influence statistical measures of the considered variables and their relationships showed that the bivariate method with empirical distributions (eeG) performed slightly better than other methods. Although the eeG method performed better than the other methods, none of the considered methods was able to fully preserve the correlation coefficient between variables detected from observations. Considering two copulas (Gaussian and Student's t), we conclude that the effect of different copula types on method performance is small.
Seasonal circulation regimes in the North Atlantic: Towards a new seasonality
Authors: Breton Florentin , Vrac Mathieu , Yiou Pascal , Vaittinada Ayar Pradeebane , Jézéquel Aglaé 
Published: February 2022

AbstractEuropean climate variability is shaped by atmospheric dynamics over the North Atlantic and local processes. Better understanding their future seasonality is essential to anticipate changes in weather conditions for human and natural systems. We explore atmospheric seasonality over 1979–2017 and 1979–2100 with seasonal circulation regimes (SCRs), by clustering year‐round daily fields of Z500 from the ERA‐Interim reanalysis and 12 Coupled Model Intercomparison Project phase 5 (CMIP5) climate models (historical and RCP8.5 runs). The spatial and temporal variability of SCR structures and associated patterns of surface air temperature are investigated. Climate models have biases but reproduce structures and evolutions of SCRs similar to the reanalysis over 1979–2017: decreasing frequency of winter conditions (starting later and ending earlier in the year) and the opposite for summer conditions. These changes are stronger over 1979–2100 than over 1979–2017, associated with a large increase of North Atlantic seasonal mean Z500 and temperature. When using more SCRs (more freedom in definition of seasonality), the changes over 1979–2100 correspond to a long‐term swap between SCRs, resulting in similar structures (annual cycle and spatial patterns) relative to the evolution of seasonal mean Z500 and temperature. To understand whether the evolution of SCRs is linked to uniform warming, or to changes in circulation patterns, we remove the calendar trend in the Z500 regional average to define SCRs based on detrended data (d‐SCRs). The temporal properties of d‐SCRs appear almost constant whereas their spatial patterns change, indicating that the calendar Z500 regional trend drives the evolutions of SCRs, and that changing spatial patterns in d‐SCRs account for the heterogeneity of this trend. Our study suggests that historical winter conditions will continue to decrease in the future while historical summer conditions continue to increase. However, it also suggests that the spatial and temporal patterns of SCRs would remain similar, relatively to the year‐round Z500 increase.
Predicting osteoarthritis onset and progression with 3D texture analysis of cartilage MRI DESS: 6‐Year data from osteoarthritis initiative
Authors: Väärälä Ari , Casula Victor , Peuna Arttu , Panfilov Egor , Mobasheri Ali , Haapea Marianne , Lammentausta Eveliina , Nieminen Miika T. 
Published: February 2022

AbstractIn this study, we developed a gray level co‐occurrence matrix‐based 3D texture analysis method for dual‐echo steady‐state (DESS) magnetic resonance (MR) images to be used for knee cartilage analysis in osteoarthritis (OA) studies and use it to study changes in articular cartilage between different subpopulations based on their rate of progression into radiographically confirmed OA. In total, 642 series of right knee DESS MR images at 3T were obtained from baseline, 36‐ and 72‐month follow‐ups from the OA Initiative database. At baseline, all 214 subjects included in the study had Kellgren‐Lawrence (KL) grade <2. Three groups were defined, based on time of progression into radiographic OA (ROA) (KL grades ≥2): control (no progression), fast progressor (ROA at 36 months), and slow progressor (ROA at 72 months) groups. 3D texture analysis was used to extract textural features for femoral and tibial cartilages. All textural features, in both femur and tibia, showed significant longitudinal changes across all groups and tissue layers. Most of the longitudinal changes were observed in progressors, but significant changes were observed also in controls. Differences between groups were mostly seen at baseline and 72 months. The method is sensitive to cartilage changes before and after ROA. It was able to detect longitudinal changes in controls and progressors and to distinguish cartilage alterations due to OA and aging. Moreover, it was able to distinguish controls and different progressor groups before any radiographic signs of OA and during OA. Thus, texture analysis could be used as a marker for the onset and progression of OA.
MRI‐detected extramural vascular invasion (mrEMVI) as the best predictive factor to identify candidates to total neoadjuvant therapy in locally advanced rectal cancer
Authors: Massucco Paolo , Fontana Andrea P. , Balbo Mussetto Annalisa , Desana Benedetta , Ricotti Andrea , Gonella Federica , Mineccia Michela , Cirillo Stefano , Ferrero Alessandro 
Published: February 2022

AbstractBackground and ObjectivesChemotherapy in locally advanced rectal cancer (LARC) is shifting from an adjuvant setting to a total neoadjuvant therapy (TNT) strategy, that relies on distant metastases (DM) risk prediction. This study aims to assess the accuracy of magnetic resonance imaging‐detected extramural vascular invasion (mrEMVI) as predictive factor for DM in LARC, compared with other MRI‐detected and pathologic factors.MethodsThis retrospective single‐center study analyzed data extracted from a series of consecutive patients curatively resected for rectal cancer at Mauriziano Hospital in Turin (Italy) from January 2013 to December 2018.ResultsData from 69 patients were analyzed. MrEMVI was detected in 31 (44.9%) cases. Median follow‐up was 39.9 months. DM and local recurrence occurred in 19 (27.5%) and 4 (5.8%) patients. One‐ and 3‐year cumulative incidence of DM were 32.3% (95% confidence interval [CI]: 0.17–0.49) and 56.8% (95% CI: 0.35–0.74) in the mrEMVI‐positive group and 5.4% (95% CI: 0.01–0.16) and 14.0% (95% CI: 0.05–0.27) in the mrEMVI‐negative group (log‐rank test, p < 0.001). In the multivariate analysis of MRI factors, mrEMVI was the only independent predictor of DM (HR: 3.59, CI: 1.21–10.69, p = 0.02).ConclusionsThis study confirmed that mrEMVI is a powerful predictor of DM in LARC. It should be routinely reported and considered during multidisciplinary care strategy planning.
Standardization and validation of phytometabolites by UHPLC and high‐performance thin layer chromatography for rapid quality assessment of ancient ayurvedic medicine, Mahayograj Guggul
Authors: Balkrishna Acharya , Tomer Meenu , Joshi Monali , Gujral Seema , Kumar Mishra Rajesh , Srivastava Jyotish , Varshney Anurag 
Published: February 2022

Mahayograj Guggul is an ancient ayurvedic medicine, prescribed for various joint disorders like arthritis, gout, and rheumatism. The present research was envisaged to develop a simple, sensitive, and comprehensive analytical method for standardization of Mahayograj Guggul. The analysis was conducted for gallic acid, protocatechuic acid, vanillic acid, cinnamic acid, piperine, guggulsterone‐E, and guggulsterone‐Z by high‐performance thin‐layer chromatography, and additionally ferulic acid, ellagic acid, and picroside I by ultra high‐performance liquid chromatography. These developed methods were validated as per international guidelines, and were found linear (r2 > 0.99), sensitive, precise (relative standard deviation < 5%), and accurate with recovery values (85–105%). The limit of detection and quantification were in the range of 0.11–23.6 and 0.33–71.51 μg/g. Gas chromatography tandem mass spectrometry was used to develop Mahayograj Guggul fingerprinting profile and to identify mid‐polar or nonpolar compounds. Proximate analysis was used to ascertain the functional groups present in Mahayograj Guggul. Ultra high‐performance liquid chromatography and gas chromatography tandem mass spectrometry were further employed to authenticate quality reproducibility in the active ingredients of Mahayograj Guggul in six commercial batches. Taken together, these analytical methods provide a scientific basis and reference for quality control evaluation of Mahayograj Guggul and similar traditional broad‐spectrum formulations.
Synthesis and Characterization of Cationic Hydrogels from Thiolated Copolymers for Independent Manipulation of Mechanical and Chemical Properties of Cell Substrates
Authors: Pätzold Florian , Stamm Nils , Kamps Dominic , Specht Maria , Bolduan Patrick , Dehmelt Leif , Weberskirch Ralf 
Published: February 2022

AbstractCells sense both mechanical and chemical properties in their environment and respond to these inputs with altered phenotypes. Precise and selective experimental manipulations of these environmental cues require biocompatible synthetic materials, for which multiple properties can be fine‐tuned independently from each other. For example, cells typically show critical thresholds for cell adhesion as a function of substrate parameters such as stiffness and the degree of functionalization. However, the choice of tailor‐made, defined materials to produce such cell adhesion substrates is still very limited. Here, a platform of synthetic hydrogels based on well‐defined thiolated copolymers is presented. Therefore, four disulfide crosslinked hydrogels of different composition by free radical polymerization are prepared. After cleavage with dithiothreitol, four soluble copolymers P1–P4 with 0–96% cationic monomer content are obtained. P1 and P4 are then combined with PEGDA3500 as a crosslinker, to fabricate 12 hydrogels with variable elasticity, ranging from 8.1 to 26.3 kPa and cationic group concentrations of up to 350 µmol cm−3. Systematic analysis using COS7 cells shows that all of these hydrogels are nontoxic. However, successful cell adhesion requires both a minimal elasticity and a minimal cationic group concentration.
Evaluation of improved CT‐based hardware attenuation correction in PET/MRI: Application to a 16‐channel RF breast coil
Authors: Lindemann Maike E. , Oehmigen Mark , Lanz Titus , Grafe Hong , Bruckmann Nils Martin , Umutlu Lale , Quick Harald H. 
Published: February 2022

AbstractPurposeThe aim of this study was to compare and evaluate three different bilinear conversion curves for attenuation correction (AC) of a 16‐channel radiofrequency (RF) coil in positron emission tomography/magnetic resonance (PET/MR) breast cancer imaging.MethodsThe quantitative impact of three different bilinear conversions of computed tomography (CT) data for the AC of a 16‐channel RF breast coil was systematically evaluated in phantom measurements and on n = 20 PET/MR patients with breast cancer. PET data were reconstructed four times: (1) no coil AC (C‐NAC) serving as a reference, (2) established bilinear conversion by Carney et al., (3) bilinear conversion by Paulus et al., and (4) bilinear conversion by Oehmigen et al. Relative differences in PET data were calculated.ResultsIndependent of the choice of bilinear conversion, significant gains in PET signal, compared to C‐NAC, were measurable in all phantom and patient measurements. Mean relative differences of ca. 10% in SUVmean (i.e., standardized uptake value; maximal relative differences up to 30%) due to the integration of the coil AC were calculated, compared to C‐NAC in phantom and patient measurements. Relative difference images depict that the quantitative impact of coil AC is highest in regions close to the RF coil when compared to no AC data. Bilinear conversion by Carney et al. shows a slightly overcorrection (2.9%), whereas the conversion by Paulus et al. provides a slight undercorrection of the PET images (−1.6%) in comparison to the no‐coil measurement. The bilinear conversion proposed by Oehmigen et al. provides the most appropriate AC for the breast coil in this phantom experiment (−0.2%). A total of 23 congruent lesions could be detected in all patients. All lesions could be detected in all reconstructions.ConclusionsFor the best possible PET image quality and accurate PET quantification in breast PET/MRI, the AC of MR hardware components is important. The bilinear conversion proposed by Oehmigen et al. provides the most appropriate AC for the breast coil in this study.