bluuebunny/crossref_metadata_2025_split huggingface dataset:
Ectopic targeting of CG DNA methylation in Arabidopsis with the bacterial SssI methyltransferase
Authors: Liu Wanlu , Gallego-Bartolomé Javier , Zhou Yuxing , Zhong Zhenhui , Wang Ming , Wongpalee Somsakul Pop , Gardiner Jason , Feng Suhua , Kuo Peggy Hsuanyu , Jacobsen Steven E. 
Published: May 2021

AbstractThe ability to target epigenetic marks like DNA methylation to specific loci is important in both basic research and in crop plant engineering. However, heritability of targeted DNA methylation, how it impacts gene expression, and which epigenetic features are required for proper establishment are mostly unknown. Here, we show that targeting the CG-specific methyltransferase M.SssI with an artificial zinc finger protein can establish heritable CG methylation and silencing of a targeted locus in Arabidopsis. In addition, we observe highly heritable widespread ectopic CG methylation mainly over euchromatic regions. This hypermethylation shows little effect on transcription while it triggers a mild but significant reduction in the accumulation of H2A.Z and H3K27me3. Moreover, ectopic methylation occurs preferentially at less open chromatin that lacks positive histone marks. These results outline general principles of the heritability and interaction of CG methylation with other epigenomic features that should help guide future efforts to engineer epigenomes.
Living supramolecular polymerization of fluorinated cyclohexanes
Authors: Shyshov Oleksandr , Haridas Shyamkumar Vadakket , Pesce Luca , Qi Haoyuan , Gardin Andrea , Bochicchio Davide , Kaiser Ute , Pavan Giovanni M. , von Delius Max 
Published: May 2021

AbstractThe development of powerful methods for living covalent polymerization has been a key driver of progress in organic materials science. While there have been remarkable reports on living supramolecular polymerization recently, the scope of monomers is still narrow and a simple solution to the problem is elusive. Here we report a minimalistic molecular platform for living supramolecular polymerization that is based on the unique structure of all-cis 1,2,3,4,5,6-hexafluorocyclohexane, the most polar aliphatic compound reported to date. We use this large dipole moment (6.2 Debye) not only to thermodynamically drive the self-assembly of supramolecular polymers, but also to generate kinetically trapped monomeric states. Upon addition of well-defined seeds, we observed that the dormant monomers engage in a kinetically controlled supramolecular polymerization. The obtained nanofibers have an unusual double helical structure and their length can be controlled by the ratio between seeds and monomers. The successful preparation of supramolecular block copolymers demonstrates the versatility of the approach.
Impacts of social distancing policies on mobility and COVID-19 case growth in the US
Authors: Wellenius Gregory A. , Vispute Swapnil , Espinosa Valeria , Fabrikant Alex , Tsai Thomas C. , Hennessy Jonathan , Dai Andrew , Williams Brian , Gadepalli Krishna , Boulanger Adam , Pearce Adam , Kamath Chaitanya , Schlosberg Arran , Bendebury Catherine , Mandayam Chinmoy , Stanton Charlotte , Bavadekar Shailesh , Pluntke Christopher , Desfontaines Damien , Jacobson Benjamin H. , Armstrong Zan , Gipson Bryant , Wilson Royce , Widdowson Andrew , Chou Katherine , Oplinger Andrew , Shekel Tomer , Jha Ashish K. , Gabrilovich Evgeniy 
Published: May 2021

AbstractSocial distancing remains an important strategy to combat the COVID-19 pandemic in the United States. However, the impacts of specific state-level policies on mobility and subsequent COVID-19 case trajectories have not been completely quantified. Using anonymized and aggregated mobility data from opted-in Google users, we found that state-level emergency declarations resulted in a 9.9% reduction in time spent away from places of residence. Implementation of one or more social distancing policies resulted in an additional 24.5% reduction in mobility the following week, and subsequent shelter-in-place mandates yielded an additional 29.0% reduction. Decreases in mobility were associated with substantial reductions in case growth two to four weeks later. For example, a 10% reduction in mobility was associated with a 17.5% reduction in case growth two weeks later. Given the continued reliance on social distancing policies to limit the spread of COVID-19, these results may be helpful to public health officials trying to balance infection control with the economic and social consequences of these policies.
Deep learning for bias correction of MJO prediction
Authors: Kim H. , Ham Y. G. , Joo Y. S. , Son S. W. 
Published: May 2021

AbstractProducing accurate weather prediction beyond two weeks is an urgent challenge due to its ever-increasing socioeconomic value. The Madden-Julian Oscillation (MJO), a planetary-scale tropical convective system, serves as a primary source of global subseasonal (i.e., targeting three to four weeks) predictability. During the past decades, operational forecasting systems have improved substantially, while the MJO prediction skill has not yet reached its potential predictability, partly due to the systematic errors caused by imperfect numerical models. Here, to improve the MJO prediction skill, we blend the state-of-the-art dynamical forecasts and observations with a Deep Learning bias correction method. With Deep Learning bias correction, multi-model forecast errors in MJO amplitude and phase averaged over four weeks are significantly reduced by about 90% and 77%, respectively. Most models show the greatest improvement for MJO events starting from the Indian Ocean and crossing the Maritime Continent.
How different combinations of comorbidities affect healthcare use by elderly patients with obstructive lung disease
Authors: Buja Alessandra , Bardin Andrea , Grotto Giulia , Elvini Stefania , Gallina Pietro , Zumerle Giulia , Benini Patrizia , Scibetta Domenico , Baldo Vincenzo 
Published: May 2021

AbstractPrevious research had shown the number of comorbidities is a major factor influencing the burden of care for elderly patients with obstructive lung disease (OLD). This retrospective cohort study on a large population of elderly patients (age > 65 years) with OLD in northern Italy measures the use of healthcare resources associated with the most frequent combinations of comorbidities and investigates the most common reasons for hospitalization. Total health costs, pharmacy costs, emergency department (ED) visits, outpatient visits, and hospital admissions are assessed for every subject. The most common causes of hospitalization by a number of comorbidities and the most common sets of three comorbidities are identified. For each comorbidity group, we rank a list of the most frequent causes of hospitalization, both overall and avoidable with effective ambulatory care. A small group of patients suffering from major comorbidities accounts for the use of most healthcare resources. The most frequent causes of hospitalization are respiratory failure, heart failure, chronic bronchitis, and bronchopneumonia. The most common conditions manageable with ambulatory care among causes of hospitalizations are heart failure, bacterial pneumonia, and COPD. The set of three comorbidities responsible for the highest average total costs, and the highest average number of hospitalizations and outpatient visits comprised hypertension, cardiac arrhythmias, and heart failure. The main reasons for hospitalization proved to remain linked to heart failure and acute respiratory disease, regardless of specific combinations of comorbidities. Based on these findings, specific public health interventions among patients with OLD cannot be advised on the basis of specific sets of comorbidities only.
Prediction of hemophilia A severity using a small-input machine-learning framework
Authors: Lopes Tiago J. S. , Rios Ricardo , Nogueira Tatiane , Mello Rodrigo F. 
Published: May 2021

AbstractHemophilia A is a relatively rare hereditary coagulation disorder caused by a defective F8 gene resulting in a dysfunctional Factor VIII protein (FVIII). This condition impairs the coagulation cascade, and if left untreated, it causes permanent joint damage and poses a risk of fatal intracranial hemorrhage in case of traumatic events. To develop prophylactic therapies with longer half-lives and that do not trigger the development of inhibitory antibodies, it is essential to have a deep understanding of the structure of the FVIII protein. In this study, we explored alternative ways of representing the FVIII protein structure and designed a machine-learning framework to improve the understanding of the relationship between the protein structure and the disease severity. We verified a close agreement between in silico, in vitro and clinical data. Finally, we predicted the severity of all possible mutations in the FVIII structure – including those not yet reported in the medical literature. We identified several hotspots in the FVIII structure where mutations are likely to induce detrimental effects to its activity. The combination of protein structure analysis and machine learning is a powerful approach to predict and understand the effects of mutations on the disease outcome.
Personalized intervention cardiology with transcatheter aortic valve replacement made possible with a non-invasive monitoring and diagnostic framework
Authors: Khodaei Seyedvahid , Henstock Alison , Sadeghi Reza , Sellers Stephanie , Blanke Philipp , Leipsic Jonathon , Emadi Ali , Keshavarz-Motamed Zahra 
Published: May 2021

AbstractOne of the most common acute and chronic cardiovascular disease conditions is aortic stenosis, a disease in which the aortic valve is damaged and can no longer function properly. Moreover, aortic stenosis commonly exists in combination with other conditions causing so many patients suffer from the most general and fundamentally challenging condition: complex valvular, ventricular and vascular disease (C3VD). Transcatheter aortic valve replacement (TAVR) is a new less invasive intervention and is a growing alternative for patients with aortic stenosis. Although blood flow quantification is critical for accurate and early diagnosis of C3VD in both pre and post-TAVR, proper diagnostic methods are still lacking because the fluid-dynamics methods that can be used as engines of new diagnostic tools are not well developed yet. Despite remarkable advances in medical imaging, imaging on its own is not enough to quantify the blood flow effectively. Moreover, understanding of C3VD in both pre and post-TAVR and its progression has been hindered by the absence of a proper non-invasive tool for the assessment of the cardiovascular function. To enable the development of new non-invasive diagnostic methods, we developed an innovative image-based patient-specific computational fluid dynamics framework for patients with C3VD who undergo TAVR to quantify metrics of: (1) global circulatory function; (2) global cardiac function as well as (3) local cardiac fluid dynamics. This framework is based on an innovative non-invasive Doppler-based patient-specific lumped-parameter algorithm and a 3-D strongly-coupled fluid-solid interaction. We validated the framework against clinical cardiac catheterization and Doppler echocardiographic measurements and demonstrated its diagnostic utility by providing novel analyses and interpretations of clinical data in eleven C3VD patients in pre and post-TAVR status. Our findings position this framework as a promising new non-invasive diagnostic tool that can provide blood flow metrics while posing no risk to the patient. The diagnostic information, that the framework can provide, is vitally needed to improve clinical outcomes, to assess patient risk and to plan treatment.
Using satellite imagery to evaluate precontact Aboriginal foraging habitats in the Australian Western Desert
Authors: Law W. Boone , Hiscock Peter , Ostendorf Bertram , Lewis Megan 
Published: May 2021

AbstractModern satellite imaging offers radical new insights of the challenges and opportunities confronting traditional Aboriginal ecology and land use in Australia’s Western Desert. We model the likely dynamics of historic and precontact desert land use using Earth observation data to identify the distribution of suitable foraging habitats. Suitability was modelled for an ideal environmental scenario, based on satellite observations of maximal water abundance, vegetation greenness, and terrain ruggedness. Our model shows that the highest-ranked foraging habitats do not align with land systems or bioregions that have been used in previous reconstructions of Australian prehistory. We identify impoverished desert areas where unsuitable foraging conditions have likely persisted since early in the last glacial cycle, and in which occupation would always have been rare. These findings lead us to reconsider past patterns of land use and the predicted archaeological signature of earlier desert peoples.
Visualizing the electron’s quantization with a ruler
Authors: Marmolejo Javier Tello , Urquiza-González Mitzi , Isaksson Oscar , Johansson Andreas , Méndez-Fragoso Ricardo , Hanstorp Dag 
Published: May 2021

AbstractMore than 100 years ago, Robert Millikan demonstrated the quantization of the electron using charged, falling droplets, but the statistical analysis on many falling droplets did not allow a direct visualization of the quantization of charge. Instead of letting the droplets fall, we have used optical levitation to create a single droplet version of Millikan’s experiment where the effects of a single electron removal can be observed by the naked eye and measured with a ruler. As we added charges to the levitated droplet, we observed that its equilibrium position jumped vertically in quantized steps. The discrete nature of the droplet’s jumps is a direct consequence of the single-electron changes in the charge on the droplet, and therefore clearly demonstrates the quantization of charge. The steps were optically magnified onto a wall and filmed. We anticipate that the video of these single electron additions can become a straightforward demonstration of the quantization of charge for a general audience.
Elastic transformation of histological slices allows precise co-registration with microCT data sets for a refined virtual histology approach
Authors: Albers Jonas , Svetlove Angelika , Alves Justus , Kraupner Alexander , di Lillo Francesca , Markus M. Andrea , Tromba Giuliana , Alves Frauke , Dullin Christian 
Published: May 2021

AbstractAlthough X-ray based 3D virtual histology is an emerging tool for the analysis of biological tissue, it falls short in terms of specificity when compared to conventional histology. Thus, the aim was to establish a novel approach that combines 3D information provided by microCT with high specificity that only (immuno-)histochemistry can offer. For this purpose, we developed a software frontend, which utilises an elastic transformation technique to accurately co-register various histological and immunohistochemical stainings with free propagation phase contrast synchrotron radiation microCT. We demonstrate that the precision of the overlay of both imaging modalities is significantly improved by performing our elastic registration workflow, as evidenced by calculation of the displacement index. To illustrate the need for an elastic co-registration approach we examined specimens from a mouse model of breast cancer with injected metal-based nanoparticles. Using the elastic transformation pipeline, we were able to co-localise the nanoparticles to specifically stained cells or tissue structures into their three-dimensional anatomical context. Additionally, we performed a semi-automated tissue structure and cell classification. This workflow provides new insights on histopathological analysis by combining CT specific three-dimensional information with cell/tissue specific information provided by classical histology.
Continual proteomic divergence of HepG2 cells as a consequence of long-term spheroid culture
Authors: Ellero Andrea Antonio , van den Bout Iman , Vlok Maré , Cromarty Allan Duncan , Hurrell Tracey 
Published: May 2021

AbstractThree-dimensional models are considered a powerful tool for improving the concordance between in vitro and in vivo phenotypes. However, the duration of spheroid culture may influence the degree of correlation between these counterparts. When using immortalised cell lines as model systems, the assumption for consistency and reproducibility is often made without adequate characterization or validation. It is therefore essential to define the biology of each spheroid model by investigating proteomic dynamics, which may be altered relative to culture duration. As an example, we assessed the influence of culture duration on the relative proteome abundance of HepG2 cells cultured as spheroids, which are routinely used to model aspects of the liver. Quantitative proteomic profiling of whole cell lysates labelled with tandem-mass tags was conducted using liquid chromatography-tandem mass spectrometry (LC–MS/MS). In excess of 4800 proteins were confidently identified, which were shared across three consecutive time points over 28 days. The HepG2 spheroid proteome was divergent from the monolayer proteome after 14 days in culture and continued to change over the successive culture time points. Proteins representing the recognised core hepatic proteome, cell junction, extracellular matrix, and cell adhesion proteins were found to be continually modulated.
Light-based methods for predicting circadian phase in delayed sleep–wake phase disorder
Authors: Murray Jade M. , Magee Michelle , Sletten Tracey L. , Gordon Christopher , Lovato Nicole , Ambani Krutika , Bartlett Delwyn J. , Kennaway David J. , Lack Leon C. , Grunstein Ronald R. , Lockley Steven W. , Rajaratnam Shantha M. W. , Phillips Andrew J. K. 
Published: May 2021

AbstractMethods for predicting circadian phase have been developed for healthy individuals. It is unknown whether these methods generalize to clinical populations, such as delayed sleep–wake phase disorder (DSWPD), where circadian timing is associated with functional outcomes. This study evaluated two methods for predicting dim light melatonin onset (DLMO) in 154 DSWPD patients using ~ 7 days of sleep–wake and light data: a dynamic model and a statistical model. The dynamic model has been validated in healthy individuals under both laboratory and field conditions. The statistical model was developed for this dataset and used a multiple linear regression of light exposure during phase delay/advance portions of the phase response curve, as well as sleep timing and demographic variables. Both models performed comparably well in predicting DLMO. The dynamic model predicted DLMO with root mean square error of 68 min, with predictions accurate to within ± 1 h in 58% of participants and ± 2 h in 95%. The statistical model predicted DLMO with root mean square error of 57 min, with predictions accurate to within ± 1 h in 75% of participants and ± 2 h in 96%. We conclude that circadian phase prediction from light data is a viable technique for improving screening, diagnosis, and treatment of DSWPD.
Smoke from regional wildfires alters lake ecology
Authors: Scordo Facundo , Chandra Sudeep , Suenaga Erin , Kelson Suzanne J. , Culpepper Joshua , Scaff Lucia , Tromboni Flavia , Caldwell Timothy J. , Seitz Carina , Fiorenza Juan E. , Williamson Craig E. , Sadro Steven , Rose Kevin C. , Poulson Simon R. 
Published: May 2021

AbstractWildfire smoke often covers areas larger than the burned area, yet the impacts of smoke on nearby aquatic ecosystems are understudied. In the summer of 2018, wildfire smoke covered Castle Lake (California, USA) for 55 days. We quantified the influence of smoke on the lake by comparing the physics, chemistry, productivity, and animal ecology in the prior four years (2014–2017) to the smoke year (2018). Smoke reduced incident ultraviolet-B (UV-B) radiation by 31% and photosynthetically active radiation (PAR) by 11%. Similarly, underwater UV-B and PAR decreased by 65 and 44%, respectively, and lake heat content decreased by 7%. While the nutrient limitation of primary production did not change, shallow production in the offshore habitat increased by 109%, likely due to a release from photoinhibition. In contrast, deep-water, primary production decreased and the deep-water peak in chlorophyll a did not develop, likely due to reduced PAR. Despite the structural changes in primary production, light, and temperature, we observed little significant change in zooplankton biomass, community composition, or migration pattern. Trout were absent from the littoral-benthic habitat during the smoke period. The duration and intensity of smoke influences light regimes, heat content, and productivity, with differing responses to consumers.
Reticulocalbin 3 is involved in postnatal tendon development by regulating collagen fibrillogenesis and cellular maturation
Authors: Park Na Rae , Shetye Snehal S. , Bogush Igor , Keene Douglas R. , Tufa Sara , Hudson David M. , Archer Marilyn , Qin Ling , Soslowsky Louis J. , Dyment Nathaniel A. , Joeng Kyu Sang 
Published: May 2021

AbstractTendon plays a critical role in the joint movement by transmitting force from muscle to bone. This transmission of force is facilitated by its specialized structure, which consists of highly aligned extracellular matrix consisting predominantly of type I collagen. Tenocytes, fibroblast-like tendon cells residing between the parallel collagen fibers, regulate this specialized tendon matrix. Despite the importance of collagen structure and tenocyte function, the biological mechanisms regulating fibrillogenesis and tenocyte maturation are not well understood. Here we examine the function of Reticulocalbin 3 (Rcn3) in collagen fibrillogenesis and tenocyte maturation during postnatal tendon development using a genetic mouse model. Loss of Rcn3 in tendon caused decreased tendon thickness, abnormal tendon cell maturation, and decreased mechanical properties. Interestingly, Rcn3 deficient mice exhibited a smaller collagen fibril distribution and over-hydroxylation in C-telopeptide cross-linking lysine from α1(1) chain. Additionally, the proline 3-hydroxylation sites in type I collagen were also over-hydroxylated in Rcn3 deficient mice. Our data collectively suggest that Rcn3 is a pivotal regulator of collagen fibrillogenesis and tenocyte maturation during postnatal tendon development.