bluuebunny/crossref_metadata_2025_split huggingface dataset:
The renoprotective effect of esaxerenone independent of blood pressure lowering: a post hoc mediation analysis of the ESAX-DN trial
Authors: Okuda Yasuyuki , Ito Sadayoshi , Kashihara Naoki , Shikata Kenichi , Nangaku Masaomi , Wada Takashi , Sawanobori Tomoko , Taguri Masataka 
Published: September 2022

AbstractAngiotensin-converting enzyme (ACE) inhibitors or angiotensin II receptor blockers (ARBs) are recommended as first-line drugs for hypertension with diabetic nephropathy owing to their renoprotective effect; however, their effect beyond lowering blood pressure (BP) has not been confirmed. Recent studies have shown that aldosterone plays a key role in causing renal injury; therefore, it is likely that mineralocorticoid receptor (MR) blockers inhibit aldosterone-induced renal damage in different ways from ACE inhibitors and ARBs. Therefore, we investigated the mechanism of the effect of an MR blocker on reducing the urinary albumin-to-creatinine ratio (UACR) using data from a randomized, double-blind, placebo-controlled phase 3 study (ESAX-DN) of a new nonsteroidal MR blocker, esaxerenone. This post hoc analysis used a novel statistical method to quantitatively estimate the effect of esaxerenone on UACR reduction mediated, or not mediated, by changes in systolic BP (SBP) and/or estimated glomerular filtration rate (eGFR). The proportion of the mediated effect by SBP changes to the total effect on UACR reduction was 9.8–10.7%; the UACR was reduced to 0.903–0.911 times the baseline at the end of treatment through the SBP-related pathway and to 0.422–0.426 times the baseline through the non-SBP-related pathway. Even considering both SBP and eGFR simultaneously, the proportion of the mediated effect was 21.9–28.1%. These results confirm that esaxerenone has a direct UACR-lowering effect independent of BP lowering and that its magnitude is much larger than that of the BP-dependent effect. Thus, esaxerenone could be a UACR-reducing treatment option for patients with diabetic nephropathy.
Basal ganglia engagement during REM sleep movements in Parkinson’s disease
Authors: Verma Ajay K. , Acosta Lenis Sergio Francisco , Aman Joshua E. , Sanabria David Escobar , Wang Jing , Pearson Amy , Hill Meghan , Patriat Remi , Schrock Lauren E. , Cooper Scott E. , Park Michael C. , Harel Noam , Howell Michael J. , MacKinnon Colum D. , Vitek Jerrold L. , Johnson Luke A. 
Published: September 2022

AbstractTo elucidate the role of the basal ganglia during REM sleep movements in Parkinson’s disease (PD) we recorded pallidal neural activity from four PD patients. Unlike desynchronization commonly observed during wakeful movements, beta oscillations (13–35 Hz) synchronized during REM sleep movements; furthermore, high-frequency oscillations (150–350 Hz) synchronized during movement irrespective of sleep-wake states. Our results demonstrate differential engagement of the basal ganglia during REM sleep and awake movements.
A test-retest resting, and cognitive state EEG dataset during multiple subject-driven states
Authors: Wang Yulin , Duan Wei , Dong Debo , Ding Lihong , Lei Xu 
Published: September 2022

AbstractHere we present a test-retest dataset of electroencephalogram (EEG) acquired at two resting (eyes open and eyes closed) and three subject-driven cognitive states (memory, music, subtraction) with both short-term (within 90 mins) and long-term (one-month apart) designs. 60 participants were recorded during three EEG sessions. Each session includes EEG and behavioral data along with rich samples of behavioral assessments testing demographic, sleep, emotion, mental health and the content of self-generated thoughts (mind wandering). This data enables the investigation of both intra- and inter-session variability not only limited to electrophysiological changes, but also including alterations in resting and cognitive states, at high temporal resolution. Also, this dataset is expected to add contributions to the reliability and validity of EEG measurements with open resource.
A georeferenced rRNA amplicon database of aquatic microbiomes from South America
Authors: Metz Sebastian , Huber Paula , Mateus-Barros Erick , Junger Pedro C. , de Melo Michaela , Bagatini Inessa Lacativa , Izaguirre Irina , Câmara dos Reis Mariana , Llames Maria E. , Accattatis Victoria , Quiroga María Victoria , Devercelli Melina , Schiaffino María Romina , Niño-García Juan Pablo , Bastidas Navarro Marcela , Modenutti Beatriz , Vieira Helena , Saraceno Martin , Sabio y García Carmen Alejandra , Pereira Emiliano , González-Revello Alvaro , Piccini Claudia , Unrein Fernando , Alonso Cecilia , Sarmento Hugo 
Published: September 2022

AbstractThe biogeography of bacterial communities is a key topic in Microbial Ecology. Regarding continental water, most studies are carried out in the northern hemisphere, leaving a gap on microorganism’s diversity patterns on a global scale. South America harbours approximately one third of the world’s total freshwater resources, and is one of these understudied regions. To fill this gap, we compiled 16S rRNA amplicon sequencing data of microbial communities across South America continental water ecosystems, presenting the first database µSudAqua[db]. The database contains over 866 georeferenced samples from 9 different ecoregions with contextual environmental information. For its integration and validation we constructed a curated database (µSudAqua[db.sp]) using samples sequenced by Illumina MiSeq platform with commonly used prokaryote universal primers. This comprised ~60% of the total georeferenced samples of the µSudAqua[db]. This compilation was carried out in the scope of the µSudAqua collaborative network and represents one of the most complete databases of continental water microbial communities from South America.
N addition alters growth, non-structural carbohydrates, and C:N:P stoichiometry of Reaumuria soongorica seedlings in Northwest China
Authors: Xie Tingting , Shan Lishan , Zhang Wanting 
Published: September 2022

AbstractReaumuria soongorica is an important biological barrier for ecological protection in the Gobi Desert in northwestern China, where soil nitrogen availability is low. N deposition has recently increased significantly in Gobi Desert, and the responses of R. soongorica to N enrichment may become a problem for ecological restoration and protection. However, little is known about the effects of N addition on the biomass, non-structural carbohydrates (NSC), and carbon:nitrogen:phosphorus (C:N:P) stoichiometry of R. soongorica in this region. Here, we examined changes in biomass, NSC and C:N:P ratios of different organs of R. soongorica seedlings in four N addition treatments: 0 (N0), 4.6 (N1), 9.2 (N2), and 13.8 (N3) g m−2 year−1. N addition up to 9.2 g m−2 year−1 significantly increased the biomass of different organs, simultaneously increasing the belowground: aboveground ratio of R. soongorica seedlings. Root NSC concentrations significantly increased under all N addition treatments, but leaf and stem NSC concentrations only increased under the N1 and N2 addition treatments. Nitrogen addition enhanced the soluble sugar concentrations (SSC) of leaves and roots, and reduced starch concentrations (SC) of all organs. Stem and root N concentrations significantly increased under the N2 and N3 treatments, and leaf N concentrations only increased under the N3 treatment, but N addition had no significant effect on plant C and P concentrations. Leaf and stem C:N ratios decreased significantly under the N2 and N3 treatments, but root C:N decreased significantly in all N addition treatments. The N3 treatment significantly increased the N:P ratio of all organs. N addition significantly enhanced available N (AN), available P (AP) and total phosphorus (TP) in rhizosphere soil. Our results suggest that N addition alters the biomass, NSC, N concentrations, C:N and N:P ratios of all plant organs, but roots responded more strongly than stems or leaves to N addition, potentially allowing the plants to absorb more water from the arid soil in this region ensuring the survival of R. soongorica seedlings. Rhizosphere soil AP, AN and TP concentrations were important factors affecting the NSC concentrations and stoichiometric characteristics of R. soongorica.
Neural network training method for materials science based on multi-source databases
Authors: Guo Jialong , Chen Ziyi , Liu Zhiwei , Li Xianwei , Xie Zhiyuan , Wang Zongguo , Wang Yangang 
Published: September 2022

AbstractThe fourth paradigm of science has achieved great success in material discovery and it highlights the sharing and interoperability of data. However, most material data are scattered among various research institutions, and a big data transmission will consume significant bandwidth and tremendous time. At the meanwhile, some data owners prefer to protect the data and keep their initiative in the cooperation. This dilemma gradually leads to the “data island” problem, especially in material science. To attack the problem and make full use of the material data, we propose a new strategy of neural network training based on multi-source databases. In the whole training process, only model parameters are exchanged and no any external access or connection to the local databases. We demonstrate its validity by training a model characterizing material structure and its corresponding formation energy, based on two and four local databases, respectively. The results show that the obtained model accuracy trained by this method is almost the same to that obtained from a single database combining all the local ones. Moreover, different communication frequencies between the client and server are also studied to improve the model training efficiency, and an optimal frequency is recommended.
FDG-PET/CT imaging parameters for predicting spontaneous regression of methotrexate-associated lymphoproliferative disorder in patients with rheumatoid arthritis
Authors: Kameda Tomohiro , Nakashima Shusaku , Mitamura Katsuya , Yamamoto Yuka , Norikane Takashi , Shimada Hiromi , Wakiya Risa , Kato Mikiya , Miyagi Taichi , Sugihara Koichi , Mino Rina , Mizusaki Mao , Kadowaki Norimitsu , Dobashi Hiroaki 
Published: September 2022

AbstractIn this study, we investigated the usefulness of FDG-PET/CT for predicting spontaneous regression in methotrexate-associated lymphoproliferative disorder (MTX-LPD). Twenty patients with rheumatoid arthritis who were diagnosed with MTX-LPD were enrolled in the study. These patients were divided into those who showed spontaneous regression (SR group: ten patients) and those who received chemotherapy after discontinuation of MTX (CTx group: ten patients). Between-group differences in potential biomarkers were compared, including clinical markers at the onset of LPD [serum LDH and interleukin 2 receptor (sIL-2R)], change in absolute number of peripheral lymphocytes (ΔALC) over follow-up, and the FDG-PET/CT-derived parameters of maximum standardized uptake value (SUVmax), mean SUV (SUVmean), peak SUV (SUVpeak), sum of the metabolic tumor volume (MTVsum), and sum of total lesion glycolysis (TLGsum). The levels of sIL-2R, MTVsum, and TLGsum were significantly lower in the SR group than in the CTx group. In addition, ΔALC was higher in the SR group. In conclusion, MTV and TLG values measured by FDG-PET/CT may be suitable for use as predictors of SR in patients with MTX-LPD.
Impact of autologous HSCT on the quality of life and fatigue in patients with relapsing multiple sclerosis
Authors: Giedraitiene N. , Gasciauskaite G. , Kaubrys G. 
Published: September 2022

AbstractIn this study, we aimed to assess the quality of life, fatigue, anxiety, and depression after Autologous haematopoietic stem cell transplantation (AHSCT) and to investigate its impact of on separate domains of health status and fatigue in patients with multiple sclerosis (MS). Overall, 18 patients with highly active relapsing MS (mean age 36.3 years, 83.3% female) underwent the AHSCT in Vilnius Multiple Sclerosis center, and we prospectively collected Short Form 36, Health Survey Questionnaire, Fatigue Descriptive Scale, and Hospital Anxiety and Depression Scale beforeand Month3, 12, and 24 after AHSCT. The median score of Expanded Disability Status Scale at Month3 after transplant improved in 14 patients (77.8%). A significant improvement in physical functioning, vitality, and pain was found at Month3 after AHSCT (p < 0.05), which was sustained until Month12 and 24. The improvement in fatigue score was found at Month12 after AHSCT, which was sustained until Month24. Decrease in EDSS score had a positive impact on the better HRQoL outcomes, especially physical and social outcomes. Thus, AHSCT improved quality of life and reduced symptoms of fatigue in patients with highly active relapsing MS. The improvement was determined earlier in the domains of QoL than in the fatigue.
Detection of urban trees sensitivity to air pollution using physiological and biochemical leaf traits in Tehran, Iran
Authors: Dadkhah-Aghdash Hamed , Rasouli Milad , Rasouli Kabir , Salimi Azam 
Published: September 2022

AbstractThe increased population in megacities has recently exacerbated the need to combat air pollution. This study examined the concept that the sensitivity and tolerance of urban plant species to air pollution might be used to determine Tehran, Iran's air quality and obtain suitable urban greening. The air pollution tolerance index (APTI) was derived using the total chlorophyll, relative water content, pH, and ascorbic acid content of leaf extract fromMorus alba,Ailanthus altissima, andSalix babylonicatrees as an indicator of the sensitivity and tolerance of urban plant species.A. altissimaandS. babylonica, with APTI values of 11.15 and 11.08, respectively, were sensitive to air pollution and can be employed as bioindicators, whereasM. alba, with an APTI value of 14.08, exhibited moderate resistance to air pollution and is therefore recommended for urban planting. Furthermore, the content of enzymatic and non-enzymatic parameters (carotenoid, phenol, and flavonoids) and proline concentration in the polluted seasons and sites (3 and 4) have been increased inM. alba. Collectively, we expect our findings to contribute to the rapidly growing body of research aiming to find a suitable urban greening for a wide range of polluted megacities.
Viewpoints on the Implications of Over-The-Counter Hearing Aids
Authors: Coco Laura , Strom Karl , Cavitt Kim , Eberts Shari , Johnson Jani A. 
Published: September 2022

Purpose:
The purpose of this article is to offer diverse viewpoints on the potential impact of over-the-counter (OTC) hearing aids on patients and hearing health care professionals. OTC hearing aids are discussed from the perspective of an editor of a hearing industry trade publication, an audiologist and business owner, a hearing aid user and consumer advocate, and a researcher and professor.

Conclusions:
Given the increasing attention surrounding OTCs, there is a need to understand diverse perspectives. The editor provides a historical context and overview of the Food and Drug Administration's OTC regulations and reflects on implications based on nearly 3 decades of experience reporting on the hearing industry. An audiologist provides her perspective on what she has observed among clinicians who appear to either resist or embrace the OTC hearing aid concept and offers recommendations for how to engage with OTCs for the benefit of patients. A hearing aid user and consumer advocate shares how OTCs might impact her own hearing care and comments on how audiologists can support consumers who choose OTCs. Lastly, a researcher offers her response to common concerns based in the literature and comments on the perceived value of OTC hearing aids. This article is concluded with a discussion on future areas of need and recommendations.
A radar waveform recognition method based on ambiguity function generative adversarial network data enhancement under the condition of small samples
Authors: Wang Haijun , Hu Tao , Xu Zhongfu , Wu Di , Dai Huanyao , Lv Pinpin , Zhang Yage , Wang Zewen 
Published: September 2022

AbstractThis study proposes a small sample recognition method for radar waveforms based on data enhancement of ambiguity function generative adversarial networks (AFGAN) to address the issue of low recognition rate and unbalanced class recognition rate. First, the concept of ambiguity function efficient contour lines (AFECL) and AFECL subject resolution constant are proposed in order to effectively extract radar waveform features. Based on this, the AFGAN model is proposed for radar waveform data enhancement. Simulation experiments classified and identified six types of radar waveforms, which verifies the effectiveness of the model. The experimental results show that the overall recognition rate is increased by 18.64%–99.25% and the class recognition unbalance is reduced by 40.67%–1.33% under the condition of small samples. Compared with short‐time Fourier transform (STFT) and Wigner‐Ville distribution (WVD), the proposed AFECL features are more suitable for recognition in small samples, and the AFGAN model performs significantly better than that of the classical data enhancement models GAN and general WGAN‐GP. The signal recognition rate reached 94.28% when the SNR was −8 dB. The effectiveness of the AFGAN data enhancement method is verified using comparative experiments.
Precision electron measurements in the solar wind at 1 au from NASA’s Wind spacecraft
Authors: Salem Chadi S. , Pulupa Marc , Bale Stuart D. , Verscharen Daniel 
Published: September 2022

Context. The non-equilibrium characteristics of electron velocity distribution functions (eVDFs) in the solar wind are key to understanding the overall plasma thermodynamics as well as the origin of the solar wind. More generally, they are important in understanding heat conduction and energy transport in all weakly collisional plasmas. Solar wind electrons are not in local thermodynamic equilibrium, and their multicomponent eVDFs develop various non-thermal characteristics, such as velocity drifts in the proton frame and temperature anisotropies as well as suprathermal tails and heat fluxes along the local magnetic field direction.
Aims. This work aims to characterize precisely and systematically the nonthermal characteristics of the eVDF in the solar wind at 1 au using data from the Wind spacecraft.
Methods. We present a comprehensive statistical analysis of solar wind electrons at 1 au using the electron analyzers of the 3D-Plasma instrument on board Wind. This work uses a sophisticated algorithm developed to analyze and characterize separately the three populations – core, halo and strahl – of the eVDF up to super-halo energies (2 keV). This algorithm calibrates these electron measurements with independent electron parameters obtained from the quasi-thermal noise around the electron plasma frequency measured by Wind’s Thermal Noise Receiver (TNR). The code determines the respective set of total electron, core, halo, and strahl parameters through non-linear least-square fits to the measured eVDF, properly taking into account spacecraft charging and other instrumental effects, such as the incomplete sampling of the eVDF by particle detectors.
Results. We use four years, approximately 280 000 independent measurements, of core, halo, and strahl electron parameters to investigate the statistical properties of these different populations in the slow and fast solar wind. We discuss the distributions of their respective densities, drift velocities, temperature, and temperature anisotropies as functions of solar wind speed. We also show distributions with solar wind speed of the total density, temperature, temperature anisotropy, and heat flux of the total eVDF, as well as those of the proton temperature, proton-to-electron temperature ratio, proton-β and electron-β. Intercorrelations between some of these parameters are also discussed.
Conclusions. The present data set represents the largest, high-precision collection of electron measurements in the pristine solar wind at 1 au. It provides a new wealth of information on electron microphysics. Its large volume will enable future statistical studies of parameter combinations and their dependences under different plasma conditions.
Automatic detection technique for solar filament oscillations in GONG data
Authors: Luna M. , Mérou Mestre J. R. , Auchère F. 
Published: September 2022

Context. Solar filament oscillations have been known for decades. The new capabilities of the new telescopes have afforded routine observations of these periodic motions. Oscillations in filaments show key aspects of their structure. A systematic study of filament oscillations over the solar cycle can shed light on the evolution of the prominences.
Aims. This work is a proof of concept that aims to automatically detect and parametrise these oscillations using Hα data from the GONG network of telescopes.
Methods. The proposed technique studies the periodic fluctuations of every pixel of the Hα data cubes. Using the fast Fourier transform, we computed the power spectral density (PSD). We defined a criterion to consider whether it is a real oscillation or a spurious fluctuation. This consisted of considering that the peak in the PSD must be greater than several times the background noise with a confidence level of 95%. The background noise is well fitted to a combination of red and white noise. We applied the method to several observations that were reported in the literature to determine its reliability. We also applied the method to a test case, which was a data set in which the oscillations of the filaments were not known a priori.
Results. The method shows that the filaments contain areas in which the PSD is above the threshold value. The periodicities we obtained generally agree with the values that were obtained by other methods. In the test case, the method detects oscillations in several filaments.
Conclusions. We conclude that the proposed spectral technique is a powerful tool for automatically detecting oscillations in prominences using Hα data.