bluuebunny/crossref_metadata_2025_split huggingface dataset:
Where Are the Proto‐South China Sea Slabs? SE Asian Plate Tectonics and Mantle Flow History From Global Mantle Convection Modeling
Authors: Lin Yi‐An , Colli Lorenzo , Wu Jonny , Schuberth Bernhard S. A. 
Published: November 2020

AbstractThe plate tectonic history of the hypothesized “proto‐South China Sea” (PSCS) ocean basin and surrounding SE Asia since Cenozoic times is controversial. We implement four diverse proto‐South China Sea plate reconstructions into global geodynamic models to constrain PSCS plate tectonics and possible slab locations. Our plate reconstructions consider the following: southward versus double‐sided PSCS subduction models; earlier (Eocene) or later (late Oligocene) initiation of Borneo counterclockwise rotations; and larger or smaller reconstructed Philippine Sea plate sizes. We compare our modeling results against tomographic images by accounting for mineralogical effects and the finite resolution of seismic tomography. All geodynamic models reproduce the tomographically imaged Sunda slabs beneath Peninsular Malaysia, Sumatra, and Java. Southward PSCS subduction produces slabs beneath present Palawan, northern Borneo, and offshore Palawan. Double‐sided PSCS subduction combined with earlier Borneo rotations uniquely reproduces subhorizontal slabs under the southern South China Sea (SCS) at ~400 to 700 km depths; these models best fit seismic tomography. A smaller Philippine Sea (PS) plate with a ~1,000‐km‐long restored Ryukyu slab was superior to a very large PS plate. Considered together, our four end‐member plate reconstructions predict that the PSCS slabs are now at <900 km depths under present‐day Borneo, the SCS, the Sulu and Celebes seas, and the southern Philippines. Regardless of plate reconstruction, we predict (1) mid‐Cenozoic passive return‐flow upwellings under Indochina; and (2) late Cenozoic downwellings under the SCS that do not support a deep‐origin “Hainan plume.” Modeled Sundaland dynamic topography strongly depends on the imposed plate reconstructions, varying by almost 1 km.
Direct‐Push Color Logging Images Spatial Heterogeneity of Organic Carbon in Floodplain Sediments
Authors: Klingler Stefan , Cirpka Olaf A. , Werban Ulrike , Leven Carsten , Dietrich Peter 
Published: November 2020

AbstractIn soils and sediments, large amounts of total organic carbon (TOC) mark reducing conditions. As dark sediment colors are good predictors for high‐TOC zones, they indicate hot spots of biogeochemical turnover and microbial activity. Traditionally, obtaining the sediment color or TOC at depth requires costly core sampling, resulting in poor horizontal resolution and related uncertainty caused by interpolation. We suggest using a direct‐push tool for optical screening of the sediment color to acquire multiple high‐resolution vertical color profiles and demonstrate its applicability to a biogeochemical transition zone in floodplain sediments, dominated by tufa. We use Gaussian mixture models for a cluster analysis of 35 color logs in the International Commission on Illumination (CIE)L*a*b* color space to identify three colorfacies that differ in lithology and TOC content: a dark colorfacies that agrees well with peat layers, a gray colorfacies associated with clay, and a creamy‐brown facies made of autochthonous carbonate precipitates. We test different approaches either to infer the TOC content from color metrics, namely, the lightness and chroma, across all facies, or to identify TOC ranges for each colorfacies. Given the high variability in TOC due to organic carbon specks in the tufa, the latter approach appears more realistic. In our application we map the 3‐D distribution of organic matter in a floodplain in distinct facies over 20,000 m2down to 12 m depth. While we relate the sediment color only to the TOC content, direct‐push color logging may also be used for in situ mapping of other biogeochemically relevant properties, such as the ferric‐iron content or sedimentary structure.
Abandonment of Penguin Subcolonies in the Late Nineteenth Century on Inexpressible Island, Antarctica
Authors: Xu Q. B. , Gao Y. S. , Yang L. J. , Yang W. Q. , Chu Z. D. , Wang Y. H. , Sun L. G. , Xie Z. Q. 
Published: November 2020

AbstractThe impact of climate and weather on penguin ecology has attracted much research attention. To reconstruct the history of the penguin population, penguin carcasses on the surface and three ornithogenic sediment profiles were collected in a ditch area beneath abandoned penguin subcolonies on a high terrace to the northwest of the modern colony in Seaview Bay, on Inexpressible Island, East Antarctica. A rapid increase in penguin‐derived element contents in the sediment profiles at ~1700 Common Era (CE) indicates an increase in the penguin population of research area at the end of the Little Ice Age. However, surficial carcasses, geochemical characteristics of the sediment profiles, and field evidence indicate the subsequent abandonment of these penguin subcolonies. A period of intensified streamflow activity resulting from meltwater is a possible explanation for the colony abandonment. The dating results of the carcasses and sediment profiles constrain this event to around the late nineteenth century. The meltwater streams can be attributed to the interaction between enhanced moist air mass transport to the coastline of Victoria Land, rising temperatures, and the sloping topography. Comparisons with other regional records suggest that this type of event is common across East Antarctica and has significant impacts on penguin ecology.
MRBLES 2.0: High-throughput generation of chemically functionalized spectrally and magnetically encoded hydrogel beads using a simple single-layer microfluidic device
Authors: Feng Yinnian , White Adam K. , Hein Jamin B. , Appel Eric A. , Fordyce Polly M. 
Published: November 2020

AbstractThe widespread adoption of bead-based multiplexed bioassays requires the ability to easily synthesize encoded microspheres and conjugate analytes of interest to their surface. Here, we present a simple method (MRBLEs 2.0) for the efficient high-throughput generation of microspheres with ratiometric barcode lanthanide encoding (MRBLEs) that bear functional groups for downstream surface bioconjugation. Bead production in MRBLEs 2.0 relies on the manual mixing of lanthanide/polymer mixtures (each of which comprises a unique spectral code) followed by droplet generation using single-layer, parallel flow-focusing devices and the off-chip batch polymerization of droplets into beads. To streamline downstream analyte coupling, MRBLEs 2.0 crosslinks copolymers bearing functional groups on the bead surface during bead generation. Using the MRBLEs 2.0 pipeline, we generate monodisperse MRBLEs containing 48 distinct well-resolved spectral codes with high throughput (>150,000/min and can be boosted to 450,000/min). We further demonstrate the efficient conjugation of oligonucleotides and entire proteins to carboxyl MRBLEs and of biotin to amino MRBLEs. Finally, we show that MRBLEs can also be magnetized via the simultaneous incorporation of magnetic nanoparticles with only a minor decrease in the potential code space. With the advantages of dramatically simplified device fabrication, elimination of the need for custom-made equipment, and the ability to produce spectrally and magnetically encoded beads with direct surface functionalization with high throughput, MRBLEs 2.0 can be directly applied by many labs towards a wide variety of downstream assays, from basic biology to diagnostics and other translational research.
Modulating proteasome inhibitor tolerance in multiple myeloma: an alternative strategy to reverse inevitable resistance
Authors: Ge Maolin , Qiao Zhi , Kong Yan , Liang Hongyu , Sun Yan , Lu Hui , Xu Zhenshu , Liu Han 
Published: November 2020

Abstract
Background
Resistance to proteasome inhibitors (PIs) is a major obstacle to the successful treatment of multiple myeloma (MM). Many mechanisms have been proposed for PI resistance; however, our mechanistic understanding of how PI resistance is inevitably acquired and reversed remains incomplete.

Methods
MM patients after bortezomib relapse, MM cell lines and mouse models were used to generate matched resistant and reversed cells. RNA sequencing and bioinformatics analyses were employed to assess dysregulated epigenetic regulators. In vitro and in vivo procedures were used to characterise PI-tolerant cells and therapeutic efficacy.

Results
Upon PI treatment, MM cells enter a slow-cycling and reversible drug-tolerant state. This reversible phenotype is associated with epigenetic plasticity, which involves tolerance rather than persistence in patients with relapsed MM. Combination treatment with histone deacetylase inhibitors and high-dosage intermittent therapy, as opposed to sustained PI monotherapy, can be more effective in treating MM by preventing the emergence of PI-tolerant cells. The therapeutic basis is the reversal of dysregulated epigenetic regulators in MM patients.

Conclusions
We propose an alternative non-mutational PI resistance mechanism that explains why PI relapse is inevitable and why patients regain sensitivity after a ‘drug holiday’. Our study also suggests strategies for epigenetic elimination of drug-tolerant cells.
New Consensus pattern in Spike CoV-2: potential implications in coagulation process and cell–cell fusion
Authors: Buonvino Silvia , Melino Sonia 
Published: November 2020

AbstractCoagulopathy and syncytial formation are relevant effects of the SARS-CoV-2 infection, but the underlying molecular mechanisms triggering these processes are not fully elucidated. Here, we identified a potential consensus pattern in the Spike S glycoprotein present within the cytoplasmic domain; this consensus pattern was detected in only 79 out of 561,000 proteins (UniProt bank). Interestingly, the pattern was present in both human and bat the coronaviruses S proteins, in many proteins involved in coagulation process, cell–cell interaction, protein aggregation and regulation of cell fate, such as von Willebrand factor, coagulation factor X, fibronectin and Notch, characterized by the presence of the cysteine-rich EGF-like domain. This finding may suggest functional similarities between the matched proteins and the CoV-2 S protein, implying a new possible involvement of the S protein in the molecular mechanism that leads to the coagulopathy and cell fusion in COVID-19 disease.
Persistence and progression of staphylococcal infection in the presence of public goods
Authors: Trivedi Urvish , Fell Cody , Madsen Jonas S. , Everett Jake , Burmølle Mette , Rumbaugh Kendra P. , Sørensen Søren J. 
Published: November 2020

AbstractStaphylococcus aureusis a prominent etiological agent of suppurative abscesses. In principle, abscess formation and purulent exudate are classical physiological features of healing and tissue repair. However,S. aureusdeploys two coagulases that can usurp this classical host response and form distinct abscess lesions. Here, we establish that during coinfection with coagulase producers and non-producers, coagulases are shared public goods that contribute to staphylococcal persistence, abscess formation, and disease progression. Coagulase-negative mutants that do not produce the public goods themselves are able to exploit those cooperatively secreted by producers and thereby thrive during coinfection at the expense of others. This study shows the importance of social interactions among pathogens concerning clinical outcomes.
Attachment and antibiotic response of early-stage biofilms studied using resonant hyperspectral imaging
Authors: Wang Yue , Reardon Christopher P. , Read Nicholas , Thorpe Stephen , Evans Adrian , Todd Neil , Van Der Woude Marjan , Krauss Thomas F. 
Published: November 2020

AbstractMany bacterial species readily develop biofilms that act as a protective matrix against external challenge, e.g., from antimicrobial treatment. Therefore, biofilms are often responsible for persistent and recurring infections. Established methods for studying biofilms are either destructive or focus on the biofilm’s surface. A non-destructive method that is sensitive to the underside of the biofilm is highly desirable, as it allows studying the penetration of antibiotics through the film. Here, we demonstrate that the high surface sensitivity of resonant hyperspectral imaging provides this capability. The method allows us to monitor the early stages of Escherichia coli biofilm formation, cell attachment and microcolony formation, in-situ and in real-time. We study the response of the biofilm to a number of different antibiotics and verify our observations using confocal microscopy. Based on this ability to closely monitor the surface-bound cells, resonant hyperspectral imaging gives new insights into the antimicrobial resistance of biofilms.
Predicting breast cancer response to neoadjuvant treatment using multi-feature MRI: results from the I-SPY 2 TRIAL
Authors: Li Wen , Newitt David C. , Gibbs Jessica , Wilmes Lisa J. , Jones Ella F. , Arasu Vignesh A. , Strand Fredrik , Onishi Natsuko , Nguyen Alex Anh-Tu , Kornak John , Joe Bonnie N. , Price Elissa R. , Ojeda-Fournier Haydee , Eghtedari Mohammad , Zamora Kathryn W. , Woodard Stefanie A. , Umphrey Heidi , Bernreuter Wanda , Nelson Michael , Church An Ly , Bolan Patrick , Kuritza Theresa , Ward Kathleen , Morley Kevin , Wolverton Dulcy , Fountain Kelly , Lopez-Paniagua Dan , Hardesty Lara , Brandt Kathy , McDonald Elizabeth S. , Rosen Mark , Kontos Despina , Abe Hiroyuki , Sheth Deepa , Crane Erin P. , Dillis Charlotte , Sheth Pulin , Hovanessian-Larsen Linda , Bang Dae Hee , Porter Bruce , Oh Karen Y. , Jafarian Neda , Tudorica Alina , Niell Bethany L. , Drukteinis Jennifer , Newell Mary S. , Cohen Michael A. , Giurescu Marina , Berman Elise , Lehman Constance , Partridge Savannah C. , Fitzpatrick Kimberly A. , Borders Marisa H. , Yang Wei T. , Dogan Basak , Goudreau Sally , Chenevert Thomas , Yau Christina , DeMichele Angela , Berry Don , Esserman Laura J. , Hylton Nola M. 
Published: November 2020

AbstractDynamic contrast-enhanced (DCE) MRI provides both morphological and functional information regarding breast tumor response to neoadjuvant chemotherapy (NAC). The purpose of this retrospective study is to test if prediction models combining multiple MRI features outperform models with single features. Four features were quantitatively calculated in each MRI exam: functional tumor volume, longest diameter, sphericity, and contralateral background parenchymal enhancement. Logistic regression analysis was used to study the relationship between MRI variables and pathologic complete response (pCR). Predictive performance was estimated using the area under the receiver operating characteristic curve (AUC). The full cohort was stratified by hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2) status (positive or negative). A total of 384 patients (median age: 49 y/o) were included. Results showed analysis with combined features achieved higher AUCs than analysis with any feature alone. AUCs estimated for the combined versus highest AUCs among single features were 0.81 (95% confidence interval [CI]: 0.76, 0.86) versus 0.79 (95% CI: 0.73, 0.85) in the full cohort, 0.83 (95% CI: 0.77, 0.92) versus 0.73 (95% CI: 0.61, 0.84) in HR-positive/HER2-negative, 0.88 (95% CI: 0.79, 0.97) versus 0.78 (95% CI: 0.63, 0.89) in HR-positive/HER2-positive, 0.83 (95% CI not available) versus 0.75 (95% CI: 0.46, 0.81) in HR-negative/HER2-positive, and 0.82 (95% CI: 0.74, 0.91) versus 0.75 (95% CI: 0.64, 0.83) in triple negatives. Multi-feature MRI analysis improved pCR prediction over analysis of any individual feature that we examined. Additionally, the improvements in prediction were more notable when analysis was conducted according to cancer subtype.
First-principles calculations of hyperfine interaction, binding energy, and quadrupole coupling for shallow donors in silicon
Authors: Swift Michael W. , Peelaers Hartwin , Mu Sai , Morton John J. L. , Van de Walle Chris G. 
Published: November 2020

AbstractSpin qubits based on shallow donors in silicon are a promising quantum information technology with enormous potential scalability due to the existence of robust silicon-processing infrastructure. However, the most accurate theories of donor electronic structure lack predictive power because of their reliance on empirical fitting parameters, while predictive ab initio methods have so far been lacking in accuracy due to size of the donor wavefunction compared to typical simulation cells. We show that density functional theory with hybrid and traditional functionals working in tandem can bridge this gap. Our first-principles approach allows remarkable accuracy in binding energies (67 meV for bismuth and 54 meV for arsenic) without the use of empirical fitting. We also obtain reasonable hyperfine parameters (1263 MHz for Bi and 133 MHz for As) and superhyperfine parameters. We demonstrate the importance of a predictive model by showing that hydrostatic strain has much larger effect on the hyperfine structure than predicted by effective mass theory, and by elucidating the underlying mechanisms through symmetry analysis of the shallow donor charge density.
Soil bacterial community structures in relation to different oil palm management practices
Authors: Berkelmann Dirk , Schneider Dominik , Hennings Nina , Meryandini Anja , Daniel Rolf 
Published: November 2020

AbstractWe provide soil bacterial 16 S rRNA gene amplicon and geochemical data derived from an oil palm plantation management experiment. The experimental design covered two different intensities of fertilizer application and weeding practices. We sampled the topsoil of 80 plots in total and extracted DNA and RNA. 16 S rRNA gene-derived and transcript-derived amplicons were generated and sequenced to analyse community composition and beta-diversity. One year after establishing the experiment, statistically significant differences of bacterial diversity or community composition between different treatments at entire (DNA-derived) and active (RNA-derived) community level were not detected. The dominant taxa belonged to Acidobacteriota and Actinobacteriota and were more abundant in the active community compared to the entire community. Similarly, the abundant genera Candidatus Solibacter and Haliangium were more abundant at active community level. Furthermore, clustering corresponding to the different sampling site locations was detected. Beta-diversity did not change among the treatments at DNA and RNA level. This dataset is of interest for related studies on the effect of altered management practices on soilborne communities.
A completely annotated whole slide image dataset of canine breast cancer to aid human breast cancer research
Authors: Aubreville Marc , Bertram Christof A. , Donovan Taryn A. , Marzahl Christian , Maier Andreas , Klopfleisch Robert 
Published: November 2020

AbstractCanine mammary carcinoma (CMC) has been used as a model to investigate the pathogenesis of human breast cancer and the same grading scheme is commonly used to assess tumor malignancy in both. One key component of this grading scheme is the density of mitotic figures (MF). Current publicly available datasets on human breast cancer only provide annotations for small subsets of whole slide images (WSIs). We present a novel dataset of 21 WSIs of CMC completely annotated for MF. For this, a pathologist screened all WSIs for potential MF and structures with a similar appearance. A second expert blindly assigned labels, and for non-matching labels, a third expert assigned the final labels. Additionally, we used machine learning to identify previously undetected MF. Finally, we performed representation learning and two-dimensional projection to further increase the consistency of the annotations. Our dataset consists of 13,907 MF and 36,379 hard negatives. We achieved a mean F1-score of 0.791 on the test set and of up to 0.696 on a human breast cancer dataset.
Predicting mortality for Covid-19 in the US using the delayed elasticity method
Authors: Hierro Luis Ángel , Garzón Antonio J. , Atienza-Montero Pedro , Márquez José Luis 
Published: November 2020

AbstractThe evolution of the pandemic caused by COVID-19, its high reproductive number and the associated clinical needs, is overwhelming national health systems. We propose a method for predicting the number of deaths, and which will enable the health authorities of the countries involved to plan the resources needed to face the pandemic as many days in advance as possible. We employ OLS to perform the econometric estimation. Using RMSE, MSE, MAPE, and SMAPE forecast performance measures, we select the best lagged predictor of both dependent variables. Our objective is to estimate a leading indicator of clinical needs. Having a forecast model available several days in advance can enable governments to more effectively face the gap between needs and resources triggered by the outbreak and thus reduce the deaths caused by COVID-19.
Using UNSEEN trends to detect decadal changes in 100-year precipitation extremes
Authors: Kelder T. , Müller M. , Slater L. J. , Marjoribanks T. I. , Wilby R. L. , Prudhomme C. , Bohlinger P. , Ferranti L. , Nipen T. 
Published: November 2020

AbstractSample sizes of observed climate extremes are typically too small to reliably constrain return period estimates when there is non-stationary behaviour. To increase the historical record 100-fold, we apply the UNprecedented Simulated Extreme ENsemble (UNSEEN) approach, by pooling ensemble members and lead times from the ECMWF seasonal prediction system SEAS5. We fit the GEV distribution to the UNSEEN ensemble with a time covariate to facilitate detection of changes in 100-year precipitation values over a period of 35 years (1981–2015). Applying UNSEEN trends to 3-day precipitation extremes over Western Norway substantially reduces uncertainties compared to estimates based on the observed record and returns no significant linear trend over time. For Svalbard, UNSEEN trends suggests there is a significant rise in precipitation extremes, such that the 100-year event estimated in 1981 occurs with a return period of around 40 years in 2015. We propose a suite of methods to evaluate UNSEEN and highlight paths for further developing UNSEEN trends to investigate non-stationarities in climate extremes.
Assessment of physiological signs associated with COVID-19 measured using wearable devices
Authors: Natarajan Aravind , Su Hao-Wei , Heneghan Conor 
Published: November 2020

AbstractRespiration rate, heart rate, and heart rate variability (HRV) are some health metrics that are easily measured by consumer devices, which can potentially provide early signs of illness. Furthermore, mobile applications that accompany wearable devices can be used to collect relevant self-reported symptoms and demographic data. This makes consumer devices a valuable tool in the fight against the COVID-19 pandemic. Data on 2745 subjects diagnosed with COVID-19 (active infection, PCR test) were collected from May 21 to September 11, 2020, consisting of PCR positive tests conducted between February 16 and September 9. Considering male (female) participants, 11.9% (11.2%) of the participants were asymptomatic, 48.3% (47.8%) recovered at home by themselves, 29.7% (33.7%) recovered at home with the help of someone else, 9.3% (6.6%) required hospitalization without ventilation, and 0.5% (0.4%) required ventilation. There were a total of 21 symptoms reported, and the prevalence of symptoms varies by sex. Fever was present in 59.4% of male subjects and in 52% of female subjects. Based on self-reported symptoms alone, we obtained an AUC of 0.82 ± 0.017 for the prediction of the need for hospitalization. Based on physiological signs, we obtained an AUC of 0.77 ± 0.018 for the prediction of illness on a specific day. Respiration rate and heart rate are typically elevated by illness, while HRV is decreased. Measuring these metrics, taken in conjunction with molecular-based diagnostics, may lead to better early detection and monitoring of COVID-19.