bluuebunny/crossref_metadata_2025_split huggingface dataset:
Influence of Aperiodic Non‐Tidal Atmospheric and Oceanic Loading Deformations on the Stochastic Properties of Global GNSS Vertical Land Motion Time Series
Authors: Gobron Kevin , Rebischung Paul , Van Camp Michel , Demoulin Alain , de Viron Olivier 
Published: September 2021

AbstractMonitoring vertical land motions (VLMs) at the level of 0.1 mm/yr remains one of the most challenging scientific applications of global navigation satellite systems (GNSS). Such small rates of change can result from climatic and tectonic phenomena, and their detection is important to many solid Earth‐related studies, including the prediction of coastal sea‐level change and the understanding of intraplate deformation. Reaching a level of precision allowing to detect such small signals requires a thorough understanding of the stochastic variability in GNSS VLM time series. This paper investigates how the aperiodic part of non‐tidal atmospheric and oceanic loading (NTAOL) deformations influences the stochastic properties of VLM time series. Using the time series of over 10,000 stations, we describe the impact of correcting for NTAOL deformation on 5 complementary metrics, namely: the repeatability of position residuals, the power‐spectrum of position residuals, the estimated time‐correlation properties, the corresponding velocity uncertainties, and the spatial correlation of the residuals. We show that NTAOL deformations cause a latitude‐dependent bias in white noise plus power‐law model parameter estimates. This bias is significantly mitigated when correcting for NTAOL deformation, which reduces velocity uncertainties at high latitudes by 70%. Therefore, removing NTAOL deformation before the statistical analysis of VLM time series might help to detect subtle VLM signals in these areas. Our spatial correlation analysis also reveals a seasonality in the spatial correlation of the residuals, which is reduced after removing NTAOL deformation, confirming that NTAOL is a clear source of common‐mode errors in GNSS VLM time series.
Sensitivity of Middle Atmospheric Ozone to Solar Proton Events: A Comparison Between a Climate Model and Satellites
Authors: Nilsen K. , Kero A. , Verronen P. T. , Szeląg M. E. , Kalakoski N. , Jia J. 
Published: September 2021

AbstractEnergetic particle precipitation (EPP) impact on the middle atmospheric ozone chemistry potentially plays an important role in the connection between space weather and Earth's climate system. A variant of the Whole Atmosphere Community Climate Model (WACCM‐D) implements a detailed set of ionospheric D‐region chemistry instead of a simple parameterization used in the earlier WACCM versions. This allows WACCM‐D to capture the impact of EPP in more detail. Here, we validate the ion chemistry of the WACCM‐D by analyzing the middle atmospheric ozone response to the EPP forcing during well‐known solar proton events (SPEs). We use a multi‐satellite approach to derive the middle atmospheric sensitivity for the SPE forcing as a statistical relation between the solar proton flux and the consequent ozone change. An identical sensitivity analysis is carried out for the WACCM‐D model results, enabling one‐to‐one comparison with the results derived from the satellite observations. Our results show a good agreement in the sensitivity between satellites and the WACCM‐D for nighttime conditions. For daytime conditions, we find a good agreement for the satellite data sets that include the largest SPEs (maximum proton flux pfu). However, for those satellite data‐sets with only minor and moderate SPEs, WACCM‐D tends to underestimate the sensitivity in daytime conditions. In summary, the WACCM‐D with its full ion chemistry and transportation demonstrates a realistic representation of the SPE sensitivity of ozone, and thus provides a conservative platform for long‐term EPP impact studies.
Formation of a Mesospheric Inversion Layer and the Subsequent Elevated Stratopause Associated With the Major Stratospheric Sudden Warming in 2018/19
Authors: Okui Haruka , Sato Kaoru , Koshin Dai , Watanabe Shingo 
Published: August 2021

AbstractSince 2004, following prolonged stratospheric sudden warming (SSW) events, it has been observed that the stratopause disappeared and reformed at a higher altitude, forming an elevated stratopause (ES). The relative roles of atmospheric waves in the mechanism of ES formation are still not fully understood. We performed a hindcast of the 2018/19 SSW event using a gravity‐wave (GW) permitting general circulation model that resolves the mesosphere and lower thermosphere (MLT) and analyzed dynamical phenomena throughout the entire middle atmosphere. An ES formed after the major warming on January 1, 2019. There was a marked temperature maximum in the polar upper mesosphere around December 28, 2018 prior to the disappearance of the descending stratopause associated with the SSW. This temperature structure is referred to as a mesospheric inversion layer (MIL). We show that adiabatic heating from the residual circulation driven by GW forcing (GWF) causes barotropic and/or baroclinic instability before the MIL formation, causing in situ generation of planetary waves (PWs). These PWs propagate into the MLT and exert negative (westward) forcing, which contributes to the MIL formation. Both GWF and PW forcing (PWF) above the recovered eastward jet play crucial roles in ES formation. The altitude of the recovered eastward jet, which regulates GWF and PWF height, is likely affected by the MIL structure. Simple vertical propagation from the lower atmosphere is insufficient to explain the presence of the GWs observed in this event.
Ozone and Nitrogen Dioxide Pollution in a Coastal Urban Environment: The Role of Sea Breezes, and Implications of Their Representation for Remote Sensing of Local Air Quality
Authors: Geddes Jeffrey A. , Wang Bo , Li Dan 
Published: September 2021

AbstractWe present an analysis of sea breeze conditions for the Boston region and examine their impact on the concentration of local air pollutants over the past decade. Sea breezes occur about one‐third of the days during the summer and play an important role in the spatial distribution and temporal evolution of NO2 and O3 across the urban area. Mornings preceding a sea breeze are characterized by low horizontal wind speeds, low background O3, and an accumulation of local primary emissions. Air pollution is recirculated inland during sea breezes, frequently coinciding with the highest O3 measured at the urban center. We use “Ox” (= NO2 + O3) to account for temporary O3 suppression by NO and find large horizontal gradients (differences in Ox greater than 30 ppb across less than 15 km), which are not observed on otherwise westerly or easterly prevailing days. This implies a challenge in surface monitoring networks to adequately represent the spatial variability of secondary air pollution in coastal urban areas. We investigate satellite‐based climatologies of tropospheric NO2, and find evidence of selection biases due to cloud conditions, but show that sea breeze days are well observed due to the fair weather conditions generally associated with these events. The fine scale of the sea breeze in Boston is not reliably represented by meteorological reanalyses products commonly used in chemical transport models required to provide inputs for the satellite‐based retrievals. This implies a higher systematic error in the operational retrievals on sea breeze days compared to other days.
Biobehavioral correlates of an fMRI index of striatal tissue iron in depressed patients
Authors: Price Rebecca B. , Tervo-Clemmens Brenden C. , Panny Benjamin , Degutis Michelle , Griffo Angela , Woody Mary 
Published: September 2021

AbstractDopaminergic function is a critical transdiagnostic neurophysiological dimension with broad relevance in psychiatry. Normalized T2*-weighted (nT2*w) imaging has been previously investigated as a method to quantify biological properties of tissue in the striatum (e.g., tissue iron), providing a widely available, in vivo marker with potential relevance to dopaminergic function; but no prior study to our knowledge has examined this neuroimaging marker in clinical depression. In a treatment-seeking, clinically depressed sample (n = 110), we quantified tissue iron (nT2*w) in striatal regions. We assessed test-retest reliability and correlated values with dimensional features across levels of analysis, including demographic/biological (sex, age, Body Mass Index), neuroanatomical (hippocampal atrophy, which was quantified using a recently validated machine-learning algorithm), and performance-based (Affective Go/NoGo task performance) indices with relevance to depressive neurocognition. Across patients, decreased tissue iron concentration (as indexed by higher nT2*w) in striatal regions correlated with indices of decreased cognitive-affective function on the Affective Go/NoGo task. Greater caudate nT2*w also correlated with greater hippocampal atrophy. Striatal tissue iron concentrations were robustly lower in female patients than males but gender differences did not explain relations with other neurocognitive variables. A widely available fMRI index of striatal tissue properties, which exhibited strong psychometric properties and can be readily quantified from most fMRI datasets irrespective of study-specific features such as task design, showed relevance to multiple biobehavioral markers of pathophysiology in the context of moderate-to-severe, treatment-resistant depression. Striatal tissue iron may play a role in dimensional and subgroup-specific features of depression, with implications for future research on depression heterogeneity.
Distinct systemic and mucosal immune responses during acute SARS-CoV-2 infection
Authors: Smith Nikaïa , Goncalves Pedro , Charbit Bruno , Grzelak Ludivine , Beretta Maxime , Planchais Cyril , Bruel Timothée , Rouilly Vincent , Bondet Vincent , Hadjadj Jérôme , Yatim Nader , Pere Helene , Merkling Sarah H. , Ghozlane Amine , Kernéis Solen , Rieux-Laucat Frederic , Terrier Benjamin , Schwartz Olivier , Mouquet Hugo , Duffy Darragh , Di Santo James P. 
Published: September 2021

AbstractCoordinated local mucosal and systemic immune responses following severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection either protect against coronavirus disease 2019 (COVID-19) pathologies or fail, leading to severe clinical outcomes. To understand this process, we performed an integrated analysis of SARS-CoV-2 spike-specific antibodies, cytokines, viral load and bacterial communities in paired nasopharyngeal swabs and plasma samples from a cohort of clinically distinct patients with COVID-19 during acute infection. Plasma viral load was associated with systemic inflammatory cytokines that were elevated in severe COVID-19, and also with spike-specific neutralizing antibodies. By contrast, nasopharyngeal viral load correlated with SARS-CoV-2 humoral responses but inversely with interferon responses, the latter associating with protective microbial communities. Potential pathogenic microorganisms, often implicated in secondary respiratory infections, were associated with mucosal inflammation and elevated in severe COVID-19. Our results demonstrate distinct tissue compartmentalization of SARS-CoV-2 immune responses and highlight a role for the nasopharyngeal microbiome in regulating local and systemic immunity that determines COVID-19 clinical outcomes.
Deep learning for distinguishing normal versus abnormal chest radiographs and generalization to two unseen diseases tuberculosis and COVID-19
Authors: Nabulsi Zaid , Sellergren Andrew , Jamshy Shahar , Lau Charles , Santos Edward , Kiraly Atilla P. , Ye Wenxing , Yang Jie , Pilgrim Rory , Kazemzadeh Sahar , Yu Jin , Kalidindi Sreenivasa Raju , Etemadi Mozziyar , Garcia-Vicente Florencia , Melnick David , Corrado Greg S. , Peng Lily , Eswaran Krish , Tse Daniel , Beladia Neeral , Liu Yun , Chen Po-Hsuan Cameron , Shetty Shravya 
Published: September 2021

AbstractChest radiography (CXR) is the most widely-used thoracic clinical imaging modality and is crucial for guiding the management of cardiothoracic conditions. The detection of specific CXR findings has been the main focus of several artificial intelligence (AI) systems. However, the wide range of possible CXR abnormalities makes it impractical to detect every possible condition by building multiple separate systems, each of which detects one or more pre-specified conditions. In this work, we developed and evaluated an AI system to classify CXRs as normal or abnormal. For training and tuning the system, we used a de-identified dataset of 248,445 patients from a multi-city hospital network in India. To assess generalizability, we evaluated our system using 6 international datasets from India, China, and the United States. Of these datasets, 4 focused on diseases that the AI was not trained to detect: 2 datasets with tuberculosis and 2 datasets with coronavirus disease 2019. Our results suggest that the AI system trained using a large dataset containing a diverse array of CXR abnormalities generalizes to new patient populations and unseen diseases. In a simulated workflow where the AI system prioritized abnormal cases, the turnaround time for abnormal cases reduced by 7–28%. These results represent an important step towards evaluating whether AI can be safely used to flag cases in a general setting where previously unseen abnormalities exist. Lastly, to facilitate the continued development of AI models for CXR, we release our collected labels for the publicly available dataset.
A fructosylated peptide derived from a collagen II T cell epitope for long-term treatment of arthritis (FIA-CIA) in mice
Authors: Wenhart Clara , Holthoff Hans-Peter , Reimann Andreas , Li Zhongmin , Faßbender Julia , Ungerer Martin 
Published: August 2021

AbstractRheumatoid arthritis (RA) is a systemic inflammatory autoimmune disease which affects primarily the joints. Peptides of several proteins have shown an effect in some experimental animal models of RA. We investigated arthritis development in male DBA/1 mice which were injected with bovine collagen II (bCII) and human fibrinogen (hFib) on days 0 and 21, leading to stable and reproducible disease induction in 100% of immunized mice (FIA-CIA). In a second study, two bCII—derived peptides were given three times in the course of 6 weeks after FIA-CIA induction to test for impact on arthritis. Mice were scored weekly for arthritis and anti-citrullinated peptide antibodies (ACPAs) were determined in the sera taken on days 0, 14, 35, 56 and 84. Histology of the hind paws was performed at the end of the experiment. Intravenous administration of peptide 90578, a novel fructosylated peptide derived from the immunodominant T cell epitope of bCII, at a dosage of 1 mg/kg resulted in significant beneficial effects on clinical outcome parameters and on the arthritis histology scores which was sustained over 12 weeks. Survival tended to be improved in peptide 90578-treated mice. Intravenous administration of pure soluble peptide 90578 without adjuvants is a promising approach to treat RA, with treatment starting at a time when ACPAs are already present. The results complement existing data on peptide “vaccination” of healthy animals, or on treatment using recombinant peptide expressing virus or complex biological compounds.
Functional data analysis characterizes the shapes of the first COVID-19 epidemic wave in Italy
Authors: Boschi Tobia , Di Iorio Jacopo , Testa Lorenzo , Cremona Marzia A. , Chiaromonte Francesca 
Published: August 2021

AbstractWe investigate patterns of COVID-19 mortality across 20 Italian regions and their association with mobility, positivity, and socio-demographic, infrastructural and environmental covariates. Notwithstanding limitations in accuracy and resolution of the data available from public sources, we pinpoint significant trends exploiting information in curves and shapes with Functional Data Analysis techniques. These depict two starkly different epidemics; an “exponential” one unfolding in Lombardia and the worst hit areas of the north, and a milder, “flat(tened)” one in the rest of the country—including Veneto, where cases appeared concurrently with Lombardia but aggressive testing was implemented early on. We find that mobility and positivity can predict COVID-19 mortality, also when controlling for relevant covariates. Among the latter, primary care appears to mitigate mortality, and contacts in hospitals, schools and workplaces to aggravate it. The techniques we describe could capture additional and potentially sharper signals if applied to richer data.
Soluble urokinase plasminogen activator receptor (suPAR) predicts critical illness and kidney failure in patients admitted to the intensive care unit
Authors: Reisinger Alexander C. , Niedrist Tobias , Posch Florian , Hatzl Stefan , Hackl Gerald , Prattes Juergen , Schilcher Gernot , Meißl Anna-Maria , Raggam Reinhard B. , Herrmann Markus , Eller Philipp 
Published: September 2021

AbstractSoluble urokinase plasminogen activator receptor (suPAR) is an inflammatory biomarker and risk factor for kidney diseases, with a potential prognostic value in critically ill patients. In this monocentric prospective study, we measured plasma suPAR levels immediately after ICU admission in unselected 237 consecutive patients using a turbidimetric assay. Primary objective was the prognostic value for ICU- and 28-day mortality. Secondary objectives were association with sequential organ failure assessment (SOFA) score, coagulation and inflammation markers, AKI-3 and differences in prespecified subgroups. Median suPAR levels were 8.0 ng/mL [25th-75th percentile 4.3–14.4], with lower levels in ICU survivors than non-survivors (6.7 vs. 11.6 ng/mL, p < 0.001). SuPAR levels were higher in COVID-19, kidney disease, moderate-to-severe liver disease, and sepsis. ICU mortality increased by an odds ratio (OR) of 4.7 in patients with the highest compared to lowest quartile suPAR. Kaplan–Meier overall survival estimates at 3 months were 63% and 49%, in patients with suPAR below/above 12 ng/mL (log-rank p = 0.027). Due to an observed interaction between SOFA score and suPAR, we performed a random forest method identifying cutoffs. ICU mortality was 53%, 17% and 2% in patients with a SOFA score > 7, SOFA ≤ 7 & suPAR > 8 ng/mL, and SOFA score ≤ 7 & suPAR ≤ 8 ng/mL, respectively. suPAR was a significant predictor for AKI-3 occurrence (OR per doubling 1.89, 95% CI: 1.20–2.98; p = 0.006). suPAR levels at ICU admission may offer additional value for risk stratification especially in ICU patients with moderate organ dysfunction as reflected by a SOFA score ≤ 7.
Comparison of the antiremodeling effects of losartan and mirabegron in a rat model of uremic cardiomyopathy
Authors: Kovács Zsuzsanna Z. A. , Szűcs Gergő , Freiwan Marah , Kovács Mónika G. , Márványkövi Fanni M. , Dinh Hoa , Siska Andrea , Farkas Katalin , Kovács Ferenc , Kriston András , Horváth Péter , Kővári Bence , Cserni Bálint Gábor , Cserni Gábor , Földesi Imre , Csont Tamás , Sárközy Márta 
Published: September 2021

AbstractUremic cardiomyopathy is characterized by diastolic dysfunction (DD), left ventricular hypertrophy (LVH), and fibrosis. Angiotensin-II plays a major role in the development of uremic cardiomyopathy via nitro-oxidative and inflammatory mechanisms. In heart failure, the beta-3 adrenergic receptor (β3-AR) is up-regulated and coupled to endothelial nitric oxide synthase (eNOS)-mediated pathways, exerting antiremodeling effects. We aimed to compare the antiremodeling effects of the angiotensin-II receptor blocker losartan and the β3-AR agonist mirabegron in uremic cardiomyopathy. Chronic kidney disease (CKD) was induced by 5/6th nephrectomy in male Wistar rats. Five weeks later, rats were randomized into four groups: (1) sham-operated, (2) CKD, (3) losartan-treated (10 mg/kg/day) CKD, and (4) mirabegron-treated (10 mg/kg/day) CKD groups. At week 13, echocardiographic, histologic, laboratory, qRT-PCR, and Western blot measurements proved the development of uremic cardiomyopathy with DD, LVH, fibrosis, inflammation, and reduced eNOS levels, which were significantly ameliorated by losartan. However, mirabegron showed a tendency to decrease DD and fibrosis; but eNOS expression remained reduced. In uremic cardiomyopathy, β3-AR, sarcoplasmic reticulum ATPase (SERCA), and phospholamban levels did not change irrespective of treatments. Mirabegron reduced the angiotensin-II receptor 1 expression in uremic cardiomyopathy that might explain its mild antiremodeling effects despite the unchanged expression of the β3-AR.
Characterizing the dielectric properties of carbon fiber at different processing stages
Authors: Chao Hsien-Wen , Hsu Hung-Chun , Chen Yen-Ren , Chang Tsun-Hsu 
Published: September 2021

AbstractThe polyacrylonitrile (PAN) fibers go through a series of chemical reactions in various processing temperatures/stages and finally turn into the so-called carbon fibers. Oxidization is the first stage, and it takes the largest proportion of the entire processing time for the tremendous change from a chain texture to a ladder texture. The pre-carbonization of carbon fibers is then achieved using a furnace with a higher processing temperature (typically at 700–900 °C). During the reaction processes, the color of the fibers changes from white (PAN) to light black (oxidation), and eventually to black (pre-carbonization). Characterizing the complex permittivity helps us determine the carbonization status of the fibers. This work employed the enhanced-field method (EFM) and the contour mapping method to determine the fibers’ dielectric properties for the first time. Results show that both the real and imaginary parts of permittivity increase as the processing temperature rises. The dielectric constants change from 2.82 (PAN) to 6.50 (pre-carbonization), and the loss tangents increase from 0.007 (lossless) to 0.089 (lossy). This study provides a simple and effective method for characterizing carbon fibers’ processing status and can be applied to the measurement of other fibrous materials.
Comparative analysis of therapeutic effects between medium cut-off and high flux dialyzers using metabolomics and proteomics: exploratory, prospective study in hemodialysis
Authors: Kim Hyo Jin , Seong Eun Young , Lee Wonho , Kim Suhkmann , Ahn Hee-Sung , Yeom Jeonghun , Kim Kyunggon , Kwon Chae Hwa , Song Sang Heon 
Published: August 2021

AbstractIn this single-center prospective study of 20 patients receiving maintenance hemodialysis (HD), we compared the therapeutic effects of medium cut-off (MCO) and high flux (HF) dialyzers using metabolomics and proteomics. A consecutive dialyzer membrane was used for 15-week study periods: 1st HF dialyzer, MCO dialyzer, 2nd HF dialyzer, for 5 weeks respectively. 1H-nuclear magnetic resonance was used to identify the metabolites and liquid chromatography-tandem mass spectrometry (LC–MS/MS) analysis was used to identify proteins. To compare the effects of the HF and MCO dialyzers, orthogonal projection to latent structure discriminant analysis (OPLS-DA) was performed. OPLS-DA showed that metabolite characteristics could be significantly classified by 1st HF and MCO dialyzers. The Pre-HD metabolites with variable importance in projection scores ≥ 1.0 in both 1st HF versus MCO and MCO versus 2nd HF were succinate, glutamate, and histidine. The pre-HD levels of succinate and histidine were significantly lower, while those of glutamate were significantly higher in MCO period than in the HF period. OPLS-DA of the proteome also substantially separated 1st HF and MCO periods. Plasma pre-HD levels of fibronectin 1 were significantly higher, and those of complement component 4B and retinol-binding protein 4 were significantly lower in MCO than in the 1st HF period. Interestingly, as per Ingenuity Pathway Analysis, an increase in epithelial cell proliferation and a decrease in endothelial cell apoptosis occurred during the MCO period. Overall, our results suggest that the use of MCO dialyzers results in characteristic metabolomics and proteomics profiles during HD compared with HF dialyzers, which might be related to oxidative stress, insulin resistance, complement-coagulation axis, inflammation, and nutrition.