bluuebunny/crossref_metadata_2025_split huggingface dataset:
Coordinated Observations of Rocket Exhaust Depletion: GOLD, Madrigal TEC, and Multiple Low‐Earth‐Orbit Satellites
Authors: Park Jaeheung , Rajesh P. K. , Ivarsen Magnus F. , Lin Charles C. H. , Eastes Richard W. , Chao Chi Kuang , Coster Anthea J. , Clausen Lasse , Burchill Johnathan K. 
Published: January 2022

AbstractA plasma density hole was created in the ionosphere by a rocket launch from Cape Canaveral, Florida near local sunset on 30 August 2020, which is called rocket exhaust depletion (RED). The hole persisted for several hours into the night and was observed in total electron content (TEC) maps, the Global‐scale Observations of the Limb and Disk (GOLD) imager, and multiple low‐earth‐orbit satellites. The RED created a nightglow pit in the GOLD 135.6 nm image. Swarm satellites found that the RED exhibited insignificant changes in electron/ion temperature and field‐aligned currents. On the other hand, magnetic field strength was enhanced inside the RED by a few tenths of a nanotesla. Assimilation data products of the Constellation Observing System for Meteorology, Ionosphere, and Climate 2 (COSMIC‐2) mission reveal that ionospheric slab thickness increased at the center of the RED, which is supported by combined analyses of the GOLD and TEC data. The RED did not host conspicuous substructures that are stronger and longer‐lasting than the ambient plasma did.
A Test of the Hypothesis That Syn‐Collisional Felsic Magmatism Contributes to Continental Crustal Growth Via Deep Learning Modeling and Principal Component Analysis of Big Geochemical Datasets
Authors: Lin Xin , Cicchella Domenico , Hong Jun , Meng Ganggang 
Published: January 2022

AbstractThe origin, way of growth, and compositional transition (from basaltic to andesitic) of continental crust remain enigmatic. To better understand the evolution of the Earth's crust, geoscientists have hypothesized two competing models, one is the widely accepted island‐arc model, the other is the newly proposed collision‐zone model that continental collision produces and preserves syn‐collisional Mantle‐derived Bulk‐continental‐crust‐like Granitoids (MBGs), and hence maintains net continental crust growth. Here, we tested the collision‐zone model by investigating the existence, temporal‐spatial distribution, geochemical signatures, and possible sources of the syn‐collisional MBGs. We applied deep learning (DL) algorithm and principal component analysis (PCA) to the database GEOROC and Tibetan Magmatism Database. DL successfully built a regression model of whole‐rock element compositional data and mean zircon εHf(t) data of igneous rocks. This can not only assign values to the missing Hf data, but statistically unveil the potential relations between the compositions (both isotopic and geochemical) and the possible sources of the igneous rocks. The DL and PCA enabled to recognize the MBGs and define their geochemical and isotopic fingerprints differing noticeably from arc magmas (e.g., Kohistan arc type and Tibetan adakite‐like type). Besides, our observations suggest that MBGs are common in collisional settings as a response to known collision events. Moreover, the MBGs' distinct geochemical and isotopic signatures indicate that they are likely sourced from subducted ocean crust. Our results therefore generally support evident contribution of syn‐collisional felsic magmatism to net continental crust growth. However, further refinement of the petrogenesis and estimation of the (relative) volume are critically needed.
A New Index for Snow/Ice/Ice‐Snow Discrimination Based on BRDF Characteristic Observation Data
Authors: Ji Wenzheng , Hao Xiaohua , Shao Donghang , Yang Qian , Wang Jian , Li Hongyi , Huang Guanghui 
Published: January 2022

AbstractThe field observation data of ice‐snow (the ice covered by snow) is scarce, causing a poor understanding of its characteristics and some uncertainty in ice process simulation. Using a multi‐angle observation instrument, we conducted a field investigation and measured the snow/ice/ice‐snow Bidirectional Reflectance Distribution Function. Both snow and ice have the typical feature of forwarding scattering, and the scattering intensity is governed by their properties (i.g., snow grain size, liquid water content, and transparency). The characteristics of ice‐snow are similar to snow when a small amount of fresh snow is deposited on the ice surface, but will change significantly when the surface snow is metamorphic (melt or refreezing). This change can affect the monitoring accuracy of snow and ice using remote sensing data. In this study, a Normalized Difference Ice‐Snow Index (NDISI) was developed using two bands (i.e., 1,080–1,120 nm and 1,760–1,800 nm). We applied spectra from different regions to verify the ability of NDISI and its application for distinguishing ice‐snow. This work should be helpful for the fine classification between snow, ice, and ice‐snow. It can support a more accurate simulation of ice phenology.
The Madden–Julian Oscillation in the Energy Exascale Earth System Model Version 1
Authors: Kim Daehyun , Kang Daehyun , Ahn Min‐Seop , DeMott Charlotte , Hsu Chia‐Wei , Yoo Changhyun , Leung L. Ruby , Hagos Samson , Rasch Philip J. 
Published: January 2022

AbstractThe present study examines the characteristics of the Madden–Julian Oscillation (MJO) events represented in the Energy Exascale Earth System Model version 1 (E3SMv1), DOE’s new Earth system model. The coupled E3SMv1 realistically simulates the eastward propagation of precipitation and moist static energy (MSE) anomalies associated with the MJO. As in observations, horizontal moisture advection and longwave radiative feedback are found to be the dominant processes in E3SMv1 that lead to the eastward movement and maintenance of the MJO MSE anomalies, respectively. Modulation of the diurnal cycle of precipitation in the Maritime Continent region by the MJO is also well represented in the model despite systematic biases in the magnitude and phase of the precipitation diurnal cycle. On the MJO impact over the midlatitude, E3SMv1 reasonably captures the pattern of the MJO teleconnections across the North Pacific and North America, with improvement in the performance in a high‐resolution version, despite the magnitude being a bit weaker than the observed. Regarding the interannual variability of the MJO, the El Niño‐Southern Oscillation (ENSO) modulation of the zonal extent of MJO’s eastward propagation, as well as associated changes in the mean state moisture gradient in the tropical west Pacific, are well reproduced in the model. However, MJO in E3SMv1 exhibits no sensitivity to the Quasi‐Biennial Oscillation (QBO), with the MJO propagation characteristics being almost identical between easterly QBO and westerly QBO years. Processes that have been suggested as critical to MJO simulation are also examined by utilizing recently developed process‐oriented diagnostics.
Toward a Robust, Impact‐Based, Predictive Drought Metric
Authors: Hobeichi Sanaa , Abramowitz Gab , Evans Jason P. , Ukkola Anna 
Published: January 2022

AbstractThis work presents a new approach to defining drought by establishing an empirical relationship between historical droughts (and wet spells) documented in impact reports, and a broad range of observed climate features using Random Forest (RF) models. The new drought indicator quantifies the conditional probability of drought, considering multiple drought‐related climate features and their interactive effects, and can be used for forecasting with up to 3‐month lead time. The approach was tested out‐of‐sample across several random selections of training and testing datasets, and demonstrated better predictive capabilities than commonly used drought indicators (e.g., Standardised Precipitation Index and Evaporative Demand Drought Index) in a range of performance metrics. Furthermore, it showed comparable performance to the (expert elicitation‐based) US Drought Monitor (USDM), the current state‐of‐the‐art record of historical drought in the USA. As well as providing an alternative historical drought indicator to USDM, the RF approach offers additional advantages by being automated, by providing drought information at the grid‐scale, and by having forecasting capacity. While traditional drought metrics define drought as extreme anomalies in drought‐related variables, the approach presented here reveals the full suite of circumstances that lead to impactful droughts. We highlight several combinations of climate features—such as precipitation, potential evapotranspiration, soil moisture and change in water storage—that led to drought events not detected by commonly used drought metrics. The new RF drought indicator combines meteorological, hydrological, agricultural, and socioeconomic drought, providing drought information for all impacted sectors. As a proof‐of‐concept, the RF drought indicator was trained on Texan climate data and droughts.
Sodium butyrate potentiates insulin secretion from rat islets at the expense of compromised expression of β cell identity genes
Authors: Wang Shushu , Yuan Miaomiao , Zhang Linlin , Zhu Kecheng , Sheng Chunxiang , Zhou Feiye , Xu Zhaoqian , Liu Qianqian , Liu Yun , Lu Jieli , Wang Xiao , Zhou Libin 
Published: January 2022

AbstractShort-chain fatty acids (SCFAs) produced by the gut microbiota have been well demonstrated to improve metabolic homeostasis. However, the role of SCFAs in islet function remains controversial. In the present study, none of the sodium acetate, sodium propionate, and sodium butyrate (SB) displayed acute impacts on insulin secretion from rat islets, whereas long-term incubation of the three SCFAs significantly potentiated pancreatic β cell function. RNA sequencing (RNA-seq) revealed an unusual transcriptome change in SB-treated rat islets, with the downregulation of insulin secretion pathway and β cell identity genes, including Pdx1, MafA, NeuroD1, Gck, and Slc2a2. But these β cell identity genes were not governed by the pan-HDAC inhibitor trichostatin A. Overlapping analysis of H3K27Ac ChIP-seq and RNA-seq showed that the inhibitory effect of SB on the expression of multiple β cell identity genes was independent of H3K27Ac. SB treatment increased basal oxygen consumption rate (OCR), but attenuated glucose-stimulated OCR in rat islets, without altering the expressions of genes involved in glycolysis and tricarboxylic acid cycle. SB reduced the expression of Kcnj11 (encoding KATP channel) and elevated basal intracellular calcium concentration. On the other hand, SB elicited insulin gene expression in rat islets through increasing H3K18bu occupation in its promoter, without stimulating CREB phosphorylation. These findings indicate that SB potentiates islet function as a lipid molecule at the expense of compromised expression of islet β cell identity genes.
Generalised popularity-similarity optimisation model for growing hyperbolic networks beyond two dimensions
Authors: Kovács Bianka , Balogh Sámuel G. , Palla Gergely 
Published: January 2022

AbstractHyperbolic network models have gained considerable attention in recent years, mainly due to their capability of explaining many peculiar features of real-world networks. One of the most widely known models of this type is the popularity-similarity optimisation (PSO) model, working in the native disk representation of the two-dimensional hyperbolic space and generating networks with small-world property, scale-free degree distribution, high clustering and strong community structure at the same time. With the motivation of better understanding hyperbolic random graphs, we hereby introduce the dPSO model, a generalisation of the PSO model to any arbitrary integer dimension $$d>2$$

d
>
2

. The analysis of the obtained networks shows that their major structural properties can be affected by the dimension of the underlying hyperbolic space in a non-trivial way. Our extended framework is not only interesting from a theoretical point of view but can also serve as a starting point for the generalisation of already existing two-dimensional hyperbolic embedding techniques.
Easy computation of the Bayes factor to fully quantify Occam’s razor in least-squares fitting and to guide actions
Authors: Dunstan D. J. , Crowne J. , Drew A. J. 
Published: January 2022

AbstractThe Bayes factor is the gold-standard figure of merit for comparing fits of models to data, for hypothesis selection and parameter estimation. However, it is little-used because it has been considered to be subjective, and to be computationally very intensive. A simple computational method has been known for at least 30 years, but has been dismissed as an approximation. We show here that all three criticisms are misplaced. The method should be used to complement and augment all least-squares fitting, because it can give very different, and better outcomes than classical methods. It can discriminate between models with equal numbers of parameters and equally good fits to data. It quantifies the Occam’s Razor injunction against over-fitting, and it demands that physically-meaningful parameters rejected by classical significance testing be included in the fitting, to avoid spurious precision and incorrect values for the other parameters. It strongly discourages the use of physically-meaningless parameters, thereby satisfying the Occam’s Razor injunction to use existing entities for explanation rather than multiplying new ones. More generally, as a relative probability, the Bayes factor combines naturally with other quantitative information to guide action in the absence of certain knowledge.
Phenotype–genotype correlation in patients with typical and atypical branchio-oto-renal syndrome
Authors: Masuda Masatsugu , Kanno Ayako , Nara Kiyomitsu , Mutai Hideki , Morisada Naoya , Iijima Kazumoto , Morimoto Noriko , Nakano Atsuko , Sugiuchi Tomoko , Okamoto Yasuhide , Masuda Sawako , Katsunuma Sayaka , Ogawa Kaoru , Matsunaga Tatsuo 
Published: January 2022

AbstractSome patients have an atypical form of branchio-oto-renal (BOR) syndrome, which does not satisfy the diagnostic criteria, despite carrying a pathogenic variant (P variant) or a likely pathogenic variant (LP variant) of a causative gene. P/LP variants phenotypic indices have yet to be determined in patients with typical and atypical BOR syndrome. We hypothesized that determining phenotypic and genetic differences between patients with typical and atypical BOR syndrome could inform such indices. Subjects were selected from among patients who underwent genetic testing to identify the cause of hearing loss. Patients were considered atypical when they had two major BOR diagnostic criteria, or two major criteria and one minor criterion; 22 typical and 16 atypical patients from 35 families were included. Genetic analysis of EYA1, SIX1, and SIX5 was conducted by direct sequencing and multiplex ligation-dependent probe amplification. EYA1 P/LP variants were detected in 25% and 86% of atypical and typical patients, respectively. Four EYA1 P/LP variants were novel. Branchial anomaly, inner ear anomaly, and mixed hearing loss were correlated with P/LP variants. Development of refined diagnostic criteria and phenotypic indices for atypical BOR syndrome will assist in effective detection of patients with P/LP variants among those with suspected BOR syndrome.
Induction of CTH expression in response to amino acid starvation confers resistance to anti-LAT1 therapy in MDA-MB-231 cells
Authors: Yamaga Takashi , Suehiro Junichi , Wada Youichiro , Sakurai Hiroyuki 
Published: January 2022

AbstractL type amino acid transporter 1 (LAT1) is an attractive molecular target for cancer therapy because of its overexpression in many cancer cells. JPH203, a selective LAT1 inhibitor, causes amino acid deprivation and suppresses cancer cell proliferation. However, several cancer cells showed resistance to amino acid deprivation. In this study, we aimed to elucidate the molecular mechanism of different sensitivity between 2 breast cancer cells to anti-LAT1 therapy. MDA-MB-231 cells were more resistant to growth suppression effect of JPH203 than T-47D cells (IC50 was 200 ± 12.5 μM for MDA-MB-231, and 5 ± 1.1 μM for T-47D cells; p < 0.05). Transcriptome and biochemical analysis were done in these cells in the presence/absence of JPH203. JPH203 induced intracellular amino acid deprivation stress in both cells, but it upregulated cystathionine γ lyase (CTH), an enzyme for synthesis of antioxidants, only in MDA-MB-231 cells. Moreover, siRNA-mediated CTH knockdown induced oxidative stress in response to JPH203 leading to decreased cell viability in MDA-MB-231 cells. These results suggest that activation of anti-oxidation pathways in response to amino acid deprivation confers resistance to anti-LAT1 therapy.
A longitudinal study of the association between visual impairment and income change using a national health screening cohort
Authors: Choi Hyo Geun , Lee Min Joung , Baek Sung Uk 
Published: January 2022

AbstractWe evaluated the influence of visual impairment (VI) on income change using the longitudinal database of a Korean National Health Insurance Service cohort. A total of 5292 participants ≥ 40 years old and registered as visually impaired persons were selected at a 1:4 ratio with 45,081 non-VI participants matched for age, sex, and income level. The income level of both the VI and non-VI groups increased over time. In the VI group, the income levels 3, 4 and 5 years were higher than the initial value, while the income levels from 1 through 5 years were increased each year in the non-VI group. The rate of change in income between time and VI were significant. In the subgroup analysis considering age, sex, and severity of VI, the rate of change in income were significant in < 65 years old subgroups. Regarding the severity of VI, a significant interaction was found for the mild-to-moderate VI subgroup. Although both the VI and non-VI groups showed increased income levels over 5 years, the degree of income increase in the VI group was relatively lower than that in the non-VI group. This finding was prominent in the middle-age subgroup. These results strongly suggested that VI induced an income inequality.
Assessment of patient follow-up from student-run free eye clinic to county ophthalmology clinic
Authors: Scheive Melanie , Rowe Lucas W. , Tso Hanna L. , Wurster Patrick , Kalafatis Nicholas E. , Camp David A. , Yung Chi Wah Rudy 
Published: January 2022

AbstractThe Ophthalmology Student Interest Group at Indiana University School of Medicine provides a free student-run eye screening clinic for an underserved community in Indianapolis. Patients with abnormal findings are referred to the ophthalmology service of the local county hospital for further evaluation. This retrospective chart review studied 180 patients referred from our free eye clinic to follow up at the ophthalmology service of a local county hospital from October 2013 to February 2020. This study investigated factors impacting follow-up of patients by analyzing demographics, medical history, insurance coverage, and final diagnoses at follow-up. Thirty-five (19.4%) of 180 patients successfully followed up at the local county hospital with an average time to follow-up of 14.4 (± 15.9) months. Mean patient age was 51 (± 13.6) with nearly equal numbers of males and females. The most common diagnoses at follow-up included refractive error (51.4%), cataract (45.7%), and glaucoma (28.6%). Patients with diabetes diagnoses or Healthy Indiana Plan insurance coverage had increased probability of follow-up. This study reveals gaps in timely follow-up to the local county hospital, demonstrating the current limitations of our free clinic in connecting patients to more definitive care and the need for an improved referral process.
Dietary shifts and social interactions drive temporal fluctuations of the gut microbiome from wild redfronted lemurs
Authors: Murillo Tatiana , Schneider Dominik , Fichtel Claudia , Daniel Rolf 
Published: January 2022

Abstract
Animals living in highly seasonal environments adapt their diets accordingly to changes in food availability. The gut microbiome as an active participant in the metabolization of the host’s diet should adapt and change with temporal diet fluctuations, but dietary shifts can be short-term and, hence, difficult to detect in cross-sectional studies. Therefore, we performed a longitudinal study combining repeated sampling of fecal samples with observations of feeding behavior in wild redfronted lemurs. We amplified taxonomical marker genes for assessing the bacteria, archaea, protozoa, helminths, and fungi, as well as the active bacterial community inhabiting their gut. We found that the most abundant protozoans were Trichostomatia and Trichomonadida, and the most abundant helminths were Chromadorea. We detected known members of the gut mycobiome from humans but in low abundances. The archaeal community is composed only of members of Methanomethylophilaceae. The predominant phyla in the entire bacterial community were Bacteroidota and Firmicutes while the most abundant genera harbor so far unknown bacteria. Temporal fluctuations at the entire community level were driven by consumption of fruits and flowers, and affiliative interactions. Changes in alpha diversity correlated only with the consumption of flowers and leaves. The composition of the entire and active bacterial community was not significantly different, but the most abundant taxa differed. Our study revealed that monthly changes in the bacterial community composition were linked to fruit and flower consumption and affiliative interactions. Thus, portraying the importance of longitudinal studies for understanding the adaptations and alterations of the gut microbiome to temporal fluctuations.
Development and preliminary validation of a machine learning system for thyroid dysfunction diagnosis based on routine laboratory tests
Authors: Hu Min , Asami Chikashi , Iwakura Hiroshi , Nakajima Yasuyo , Sema Ryousuke , Kikuchi Tsuyoshi , Miyata Tsuyoshi , Sakamaki Koji , Kudo Takumi , Yamada Masanobu , Akamizu Takashi , Sakakibara Yasubumi 
Published: January 2022

Abstract
Background
Approximately 2.4 million patients in Japan would benefit from treatment for thyroid disease, including Graves’ disease and Hashimoto’s disease. However, only 450,000 of them are receiving treatment, and many patients with thyroid dysfunction remain largely overlooked. In this retrospective study, we aimed to develop and conduct preliminary testing on a machine learning method for screening patients with hyperthyroidism and hypothyroidism who would benefit from prompt medical treatment.

Methods
We collected electronic medical records and medical checkup data from four hospitals in Japan. We applied four machine learning algorithms to construct classification models to distinguish patients with hyperthyroidism and hypothyroidism from control subjects using routine laboratory tests. Performance evaluation metrics such as sensitivity, specificity, and the area under receiver operating characteristic (AUROC) were obtained. Techniques such as feature importance were further applied to understand the contribution of each feature to the machine learning output.

Results
The results of cross-validation and external evaluation indicated that we achieved high classification accuracies (AUROC = 93.8% for hyperthyroidism model and AUROC = 90.9% for hypothyroidism model). Serum creatinine (S-Cr), mean corpuscular volume (MCV), and total cholesterol were the three features that were most strongly correlated with the hyperthyroidism model, and S-Cr, lactic acid dehydrogenase (LDH), and total cholesterol were correlated with the hypothyroidism model.

Conclusions
We demonstrated the potential of machine learning approaches for diagnosing the presence of thyroid dysfunction from routine laboratory tests. Further validation, including prospective clinical studies, is necessary prior to application of our method in the clinic.