bluuebunny/crossref_metadata_2025 huggingface dataset:
Dissolved Organic Radiocarbon in the Eastern Pacific and Southern Oceans
Authors: Druffel Ellen R. M. , Griffin Sheila , Lewis Christian B. , Rudresh Megha , Garcia Noreen G. , Key Robert M. , McNichol Ann P. , Hauksson Niels E. , Walker Brett D.
Published: May 2021

We report marine dissolved organic carbon (DOC) concentrations, and DOC Δ14C and δ13C values in seawater collected from the Southern Ocean and eastern Pacific GOSHIP cruise P18 in 2016/2017. The aging of 14C in DOC in circumpolar deep water northward from 69°S to 20°N was similar to that measured in dissolved inorganic carbon in the same samples, indicating that the transport of deep waters northward is the primary control of 14C in DIC and DOC. Low DOC ∆14C and δ13C measurements between 1,200 and 3,400 m depth may be evidence of a source of DOC produced in nearby hydrothermal ridge systems (East Pacific Rise).
Impacts of Continuously Increasing Urbanization Ratios on Warming Rates and Temperature Extremes Observed Over the Beijing Area
Authors: Jiang Shaojing , Du Jizeng , Wei Zhongwang
Published: May 2021

Evaluations of the impacts of increasing urbanization ratios on air temperatures are less quantitative and accurate due to the lack of high‐resolution land cover data sets. Here, based on the latest released high‐resolution (30‐m) land cover data from 1985 to 2017, annual urbanization ratios around each station in Beijing were calculated. Warming rates and temperature extremes were compared between nonrural stations (17 stations with continuously increasing urbanization ratios) and purely rural stations (3 stations with continuous urbanization ratios of zero). Although urbanized areas only occupied 22.2% of the total area in Beijing, urbanization ratios at nonrural stations already reached an average of 62.4% (10 km2)−1in 2017, and their average rate reached 15.1% (10 km2)−1 decade−1. From 1985 to 2017, each 10% increase in the urbanization ratio with 10 km2had led to additional annual warming of 0.14 ± 0.11, 0.17 ± 0.08, and 0.30 ± 0.17°C at nonrural stations for daily maximum (Tmax), mean (Tmean), and minimum (Tmin) air temperatures, respectively. Meanwhile, each 10% increase in the urbanization ratio with 10 km2had led to additional changes of 11.6 ± 5.1, 12.7 ± 5.8, and −11.1 ± 5.2 days at nonrural stations for hot days, hot nights, and chilly nights, respectively. Additionally, the inner‐annual urbanization contributions to the warming increased significantly at rates of 10.7% decade−1and 14.1% decade−1forTmeanandTmin, and reached 49.0% and 52.6% in 2017, respectively. The inner‐annual urbanization contributions to the increasing hot nights and the decreasing chilly nights changed at rates of 16.7% decade−1and 15.6% decade−1, and reached 57.8% and 53.1% in 2017, respectively.
Methods for latent image simulations in photolithography with a polychromatic light attenuation equation for fabricating VIAs in 2.5D and 3D advanced packaging architectures
Authors: Smallwood Daniel C. , McCloskey Paul , O’Mathuna Cian , Casey Declan P. , Rohan James F.
Published: May 2021

As demand accelerates for multifunctional devices with a small footprint and minimal power consumption, 2.5D and 3D advanced packaging architectures have emerged as an essential solution that use through-substrate vias (TSVs) as vertical interconnects. Vertical stacking enables chip packages with increased functionality, enhanced design versatility, minimal power loss, reduced footprint and high bandwidth. Unlocking the potential of photolithography for vertical interconnect access (VIA) fabrication requires fast and accurate predictive modeling of diffraction effects and resist film photochemistry. This procedure is especially challenging for broad-spectrum exposure systems that use, for example, Hg bulbs with g-, h-, and i-line UV radiation. In this paper, we present new methods and equations for VIA latent image determination in photolithography that are suitable for broad-spectrum exposure and negate the need for complex and time-consuming in situ metrology. Our technique is accurate, converges quickly on the average modern PC and could be readily integrated into photolithography simulation software. We derive a polychromatic light attenuation equation from the Beer-Lambert law, which can be used in a critical exposure dose model to determine the photochemical reaction state. We integrate this equation with an exact scalar diffraction formula to produce a succinct equation comprising a complete coupling between light propagation phenomena and photochemical behavior. We then perform a comparative study between 2D/3D photoresist latent image simulation geometries and directly corresponding experimental data, which demonstrates a highly positive correlation. We anticipate that this technique will be a valuable asset to photolithography, micro- and nano-optical systems and advanced packaging/system integration with applications in technology domains ranging from space to automotive to the Internet of Things (IoT).
CD52 is a novel target for the treatment of FLT3-ITD-mutated myeloid leukemia
Authors: Karnan Sivasundaram , Hanamura Ichiro , Ota Akinobu , Takasugi Souichi , Nakamura Ayano , Takahashi Miyuki , Uchino Kaori , Murakami Satsuki , Wahiduzzaman Md , Quang Vu Lam , Rahman Md Lutfur , Hasan Muhammad Nazmul , Hyodo Toshinori , Konishi Hiroyuki , Tsuzuki Shinobu , Yoshikawa Kazuhiro , Suzuki Susumu , Ueda Ryuzo , Ejiri Masayuki , Hosokawa Yoshitaka , Takami Akiyoshi
Published: May 2021

Internal tandem duplication (ITD) ofFMS-like tyrosine kinase 3(FLT3) confers poor prognosis and is found in approximately 25% of cases of acute myeloid leukemia (AML). Although FLT3 inhibitors have shown clinical benefit in patients with AML harboringFLT3-ITD, the therapeutic effect is limited. Here, to explore alternative therapeutics, we established a cellular model of monoallelicFLT3ITD/WTcells using the CRISPR-Cas9 system in a human myeloid leukemia cell line, K562. cDNA microarray analysis revealed elevatedCD52expression in K562–FLT3ITD/WTcells compared to K562–FLT3WT/WTcells, an observation that was further confirmed by quantitative real-time-PCR and flow cytometric analyses. The elevated expression ofCD52in K562–FLT3ITD/WTcells was decreased in wild-typeFLT3(FLT3-WT) knock-in K562–FLT3ITD/WTcells. In K562–FLT3ITD/WTcells, a STAT5 inhibitor, pimozide, downregulated CD52 protein expression while an AKT inhibitor, afuresertib, did not affect CD52 expression. Notably, an anti-CD52 antibody, alemtuzumab, induced significant antibody-dependent cell-mediated cytotoxicity (ADCC) in K562-FLT3ITD/WTcells compared to K562–FLT3WT/WTcells. Furthermore, alemtuzumab significantly suppressed the xenograft tumor growth of K562–FLT3ITD/WTcells in severe combined immunodeficiency (SCID) mice. Taken together, our data suggested that genetically modifiedFLT3-ITD knock-in human myeloid leukemia K562 cells upregulated CD52 expression via activation of STAT5, and alemtuzumab showed an antitumor effect via induction of ADCC in K562–FLT3ITD/WTcells. Our findings may allow establishment of a new therapeutic option, alemtuzumab, to treat leukemia with theFLT3-ITD mutation.
Single-cell analysis of pancreatic ductal adenocarcinoma identifies a novel fibroblast subtype associated with poor prognosis but better immunotherapy response
Authors: Wang Yu , Liang Yiyi , Xu Haiyan , Zhang Xiao , Mao Tiebo , Cui Jiujie , Yao Jiayu , Wang Yongchao , Jiao Feng , Xiao Xiuying , Hu Jiong , Xia Qing , Zhang Xiaofei , Wang Xujun , Sun Yongwei , Fu Deliang , Shen Lei , Xu Xiaojiang , Xue Jing , Wang Liwei
Published: May 2021

The current pathological and molecular classification of pancreatic ductal adenocarcinoma (PDAC) provides limited guidance for treatment options, especially for immunotherapy. Cancer-associated fibroblasts (CAFs) are major players of desmoplastic stroma in PDAC, modulating tumor progression and therapeutic response. Using single-cell RNA sequencing, we explored the intertumoral heterogeneity among PDAC patients with different degrees of desmoplasia. We found substantial intertumoral heterogeneity in CAFs, ductal cancer cells, and immune cells between the extremely dense and loose types of PDACs (dense-type, high desmoplasia; loose-type, low desmoplasia). Notably, no difference in CAF abundance was detected, but a novel subtype of CAFs with a highly activated metabolic state (meCAFs) was found in loose-type PDAC compared to dense-type PDAC. MeCAFs had highly active glycolysis, whereas the corresponding cancer cells used oxidative phosphorylation as a major metabolic mode rather than glycolysis. We found that the proportion and activity of immune cells were much higher in loose-type PDAC than in dense-type PDAC. Then, the clinical significance of the CAF subtypes was further validated in our PDAC cohort and a public database. PDAC patients with abundant meCAFs had a higher risk of metastasis and a poor prognosis but showed a dramatically better response to immunotherapy (64.71% objective response rate, one complete response). We characterized the intertumoral heterogeneity of cellular components, immune activity, and metabolic status between dense- and loose-type PDACs and identified meCAFs as a novel CAF subtype critical for PDAC progression and the susceptibility to immunotherapy.
Magnetoelectric coupling of domains, domain walls and vortices in a multiferroic with independent magnetic and electric order
Authors: Giraldo Marcela , Meier Quintin N. , Bortis Amadé , Nowak Dominik , Spaldin Nicola A. , Fiebig Manfred , Weber Mads C. , Lottermoser Thomas
Published: May 2021

Magnetically induced ferroelectrics exhibit rigidly coupled magnetic and electric order. The ordering temperatures and spontaneous polarization of these multiferroics are notoriously low, however. Both properties can be much larger if magnetic and ferroelectric order occur independently, but the cost of this independence is that pronounced magnetoelectric interaction is no longer obvious. Using spatially resolved images of domains and density-functional theory, we show that in multiferroics with separately emerging magnetic and ferroelectric order, the microscopic magnetoelectric coupling can be intrinsically strong even though the macroscopic leading-order magnetoelectric effect is forbidden by symmetry. We show, taking hexagonal ErMnO3 as an example, that a strong bulk coupling between the ferroelectric and antiferromagnetic order is realized because the structural distortions that lead to the ferroelectric polarization also break the balance of the competing superexchange contributions. We observe the manifestation of this coupling in uncommon types of topological defects like magnetoelectric domain walls and vortex-like singularities.
Transcranial alternating current stimulation entrains alpha oscillations by preferential phase synchronization of fast-spiking cortical neurons to stimulation waveform
Authors: Huang Wei A. , Stitt Iain M. , Negahbani Ehsan , Passey D. J. , Ahn Sangtae , Davey Marshall , Dannhauer Moritz , Doan Thien T. , Hoover Anna C. , Peterchev Angel V. , Radtke-Schuller Susanne , Fröhlich Flavio
Published: May 2021

Computational modeling and human studies suggest that transcranial alternating current stimulation (tACS) modulates alpha oscillations by entrainment. Yet, a direct examination of how tACS interacts with neuronal spiking activity that gives rise to the alpha oscillation in the thalamo-cortical system has been lacking. Here, we demonstrate how tACS entrains endogenous alpha oscillations in head-fixed awake ferrets. We first show that endogenous alpha oscillations in the posterior parietal cortex drive the primary visual cortex and the higher-order visual thalamus. Spike-field coherence is largest for the alpha frequency band, and presumed fast-spiking inhibitory interneurons exhibit strongest coupling to this oscillation. We then apply alpha-tACS that results in a field strength comparable to what is commonly used in humans (<0.5 mV/mm). Both in these ferret experiments and in a computational model of the thalamo-cortical system, tACS entrains alpha oscillations by following the theoretically predicted Arnold tongue. Intriguingly, the fast-spiking inhibitory interneurons exhibit a stronger entrainment response to tACS in both the ferret experiments and the computational model, likely due to their stronger endogenous coupling to the alpha oscillation. Our findings demonstrate the in vivo mechanism of action for the modulation of the alpha oscillation by tACS.
Ultra-compact dual-band smart NEMS magnetoelectric antennas for simultaneous wireless energy harvesting and magnetic field sensing
Authors: Zaeimbashi Mohsen , Nasrollahpour Mehdi , Khalifa Adam , Romano Anthony , Liang Xianfeng , Chen Huaihao , Sun Neville , Matyushov Alexei , Lin Hwaider , Dong Cunzheng , Xu Ziyue , Mittal Ankit , Martos-Repath Isabel , Jha Gaurav , Mirchandani Nikita , Das Diptashree , Onabajo Marvin , Shrivastava Aatmesh , Cash Sydney , Sun Nian X.
Published: May 2021

Ultra-compact wireless implantable medical devices are in great demand for healthcare applications, in particular for neural recording and stimulation. Current implantable technologies based on miniaturized micro-coils suffer from low wireless power transfer efficiency (PTE) and are not always compliant with the specific absorption rate imposed by the Federal Communications Commission. Moreover, current implantable devices are reliant on differential recording of voltage or current across space and require direct contact between electrode and tissue. Here, we show an ultra-compact dual-band smart nanoelectromechanical systems magnetoelectric (ME) antenna with a size of 250 × 174 µm2 that can efficiently perform wireless energy harvesting and sense ultra-small magnetic fields. The proposed ME antenna has a wireless PTE 1–2 orders of magnitude higher than any other reported miniaturized micro-coil, allowing the wireless IMDs to be compliant with the SAR limit. Furthermore, the antenna’s magnetic field detectivity of 300–500 pT allows the IMDs to record neural magnetic fields.
Water friction in nanofluidic channels made from two-dimensional crystals
Authors: Keerthi Ashok , Goutham Solleti , You Yi , Iamprasertkun Pawin , Dryfe Robert A. W. , Geim Andre K. , Radha Boya
Published: May 2021

Membrane-based applications such as osmotic power generation, desalination and molecular separation would benefit from decreasing water friction in nanoscale channels. However, mechanisms that allow fast water flows are not fully understood yet. Here we report angstrom-scale capillaries made from atomically flat crystals and study the effect of confining walls’ material on water friction. A massive difference is observed between channels made from isostructural graphite and hexagonal boron nitride, which is attributed to different electrostatic and chemical interactions at the solid-liquid interface. Using precision microgravimetry and ion streaming measurements, we evaluate the slip length, a measure of water friction, and investigate its possible links with electrical conductivity, wettability, surface charge and polarity of the confining walls. We also show that water friction can be controlled using hybrid capillaries with different slip lengths at opposing walls. The reported advances extend nanofluidics’ toolkit for designing smart membranes and mimicking manifold machinery of biological channels.
Synthetic neural-like computing in microbial consortia for pattern recognition
Authors: Li Ximing , Rizik Luna , Kravchik Valeriia , Khoury Maria , Korin Netanel , Daniel Ramez
Published: May 2021

Complex biological systems in nature comprise cells that act collectively to solve sophisticated tasks. Synthetic biological systems, in contrast, are designed for specific tasks, following computational principles including logic gates and analog design. Yet such approaches cannot be easily adapted for multiple tasks in biological contexts. Alternatively, artificial neural networks, comprised of flexible interactions for computation, support adaptive designs and are adopted for diverse applications. Here, motivated by the structural similarity between artificial neural networks and cellular networks, we implement neural-like computing in bacteria consortia for recognizing patterns. Specifically, receiver bacteria collectively interact with sender bacteria for decision-making through quorum sensing. Input patterns formed by chemical inducers activate senders to produce signaling molecules at varying levels. These levels, which act as weights, are programmed by tuning the sender promoter strength Furthermore, a gradient descent based algorithm that enables weights optimization was developed. Weights were experimentally examined for recognizing 3 × 3-bit pattern.
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

The 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

The 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

Social 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

Producing 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

Previous 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

Hemophilia 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

One 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

Modern 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

More 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

Although 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

Three-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

Methods 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

Wildfire 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.
Author Correction: Data suggest COVID-19 affected numbers greatly exceeded detected numbers, in four European countries, as per a delayed SEIQR model
Authors: Tiwari Sankalp , Vyasarayani C. P. , Chatterjee Anindya
Published: May 2021

An amendment to this paper has been published and can be accessed via a link at the top of the paper.
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

Tendon 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.
Deep learning for large scale MRI-based morphological phenotyping of osteoarthritis
Authors: Namiri Nikan K. , Lee Jinhee , Astuto Bruno , Liu Felix , Shah Rutwik , Majumdar Sharmila , Pedoia Valentina
Published: May 2021

Osteoarthritis (OA) develops through heterogenous pathophysiologic pathways. As a result, no regulatory agency approved disease modifying OA drugs are available to date. Stratifying knees into MRI-based morphological phenotypes may provide insight into predicting future OA incidence, leading to improved inclusion criteria and efficacy of therapeutics. We trained convolutional neural networks to classify bone, meniscus/cartilage, inflammatory, and hypertrophy phenotypes in knee MRIs from participants in the Osteoarthritis Initiative (n = 4791). We investigated cross-sectional association between baseline morphological phenotypes and baseline structural OA (Kellgren Lawrence grade > 1) and symptomatic OA. Among participants without baseline OA, we evaluated association of baseline phenotypes with 48-month incidence of structural OA and symptomatic OA. The area under the curve of bone, meniscus/cartilage, inflammatory, and hypertrophy phenotype neural network classifiers was 0.89 ± 0.01, 0.93 ± 0.03, 0.96 ± 0.02, and 0.93 ± 0.02, respectively (mean ± standard deviation). Among those with no baseline OA, bone phenotype (OR: 2.99 (95%CI: 1.59–5.62)) and hypertrophy phenotype (OR: 5.80 (95%CI: 1.82–18.5)) each respectively increased odds of developing incident structural OA and symptomatic OA at 48 months. All phenotypes except meniscus/cartilage increased odds of undergoing total knee replacement within 96 months. Artificial intelligence can rapidly stratify knees into structural phenotypes associated with incident OA and total knee replacement, which may aid in stratifying patients for clinical trials of targeted therapeutics.
Serum IGFBP-2 in systemic sclerosis as a prognostic factor of lung dysfunction
Authors: Guiot Julien , Njock Makon-Sébastien , André Béatrice , Gester Fanny , Henket Monique , de Seny Dominique , Moermans Catherine , Malaise Michel G. , Louis Renaud
Published: May 2021

Systemic sclerosis (SSc) is a rare connective tissue disease associated with rapid evolving interstitial lung disease (ILD), driving its mortality. Specific biomarkers associated with the progression of this lung disease are highly needed. We aimed to identify specific biomarkers of SSc-ILD to predict the evolution of the disease. For this, we compared prospectively serum levels of several biomarkers associated with lung fibrosis in SSc patients (n = 102), among which SSc-no ILD (n = 63) and SSc-ILD (n = 39), compared to healthy subjects (HS) (n = 39). We also performed a longitudinal study in a subgroup of 28 patients analyzing biomarkers variations and pulmonary function tests over a period of 2 years. Serum level of IGFBP-2 was significantly increased in SSc patients compared to HS, and negatively correlated with pulmonary function (assessed by carbon monoxide transfer coefficient (KCO)) (r = − 0.29, p < 0.01). Two-year longitudinal analysis in a subgroup of 28 SSc patients determined that IGFBP-2 variation was positively correlated with KCO at 2-year follow-up (r = 0.6, p < 0.001). SSc patients with a lower variation of IGFBP-2 (less than 22%) presented significant deterioration of pulmonary function at 2-year follow-up (p < 0.01). ROC curve analysis enabled us to identify that baseline IGFBP-2 > 105 ng/ml was associated with a poor outcome (KCO < 70% predicted) at 2-year follow-up (AUC = 0.75, p < 0.05). We showed for the first time that serum levels of IGFBP-2 might be a prognostic factor of the development of SSc-ILD.
Alginate hydrogel beads embedded with drug-bearing polycaprolactone microspheres for sustained release of paclobutrazol
Authors: Mun Alexandra , Simaan Yameen Haneen , Edelbaum Giora , Seliktar Dror
Published: May 2021

In recent years there has been a growing demand for the development of agrochemical controlled release (CR) technologies. In the present study, we aimed to create a novel agricultural CR device using two polymeric systems that have been predominantly employed in biomedical applications: beads of alginate hydrogel embedded with drug-bearing Polycaprolactone (PCL) microspheres. The combined device utilizes the advantages of each polymer type for biodegradation and controlled release of Paclobutrazol (PBZ), a common growth retardant in plants. Surface morphology of the alginate beads was characterized by scanning electron microscopy (SEM) and water immersion tests were performed for stability and controlled release measurements. Bioassays were performed both in accelerated laboratory conditions and in field conditions. The results showed a capability to control the size of PBZ-loaded PCL microspheres through modification of homogenization speed and emulsifier concentration. Enlargement of PCL microsphere size had an adverse effect on release of PBZ from the alginate device. The growth of oatmeal plants as a model system was affected by the controlled release of PBZ. The preliminary field experiment observed growth retardation during two consecutive rainy seasons, with results indicating a substantial benefit of the sustained growth inhibition through the controlled release formulation. The final product has the potential to be used as a carrier for different substances in the agrochemical industry.
White matter hyperintensity in different migraine subtypes
Authors: Dobrynina L. A. , Suslina A. D. , Gubanova M. V. , Belopasova A. V. , Sergeeva A. N. , Evers S. , Gnedovskaya E. V. , Krotenkova M. V.
Published: May 2021

The diagnostic value of white matter hyperintensities (WMH) in different types of migraineare unknown. To evaluate the WMH pattern of different subtypes in migraine patients with no vascular risk factors. 92 migraine patients (73 females, mean age 34.6 ± 8.9; 61 episodic migraine, 31 chronic migraine, 36 migraine with aura, 56 migraine without aura) without vascular risk factors underwent brain MRI (3 T). We also included a matched healthy control group with no migraine (n = 24). The prevalence of WMH in different types of migraine was similar and ranged from 38.7 to 44.4%; the control group showed no WMH at all. Lesions were located within frontal, parietal and temporal lobes (in order of decreasing incidence) in juxtacortical and/or deep white matter. WMH appeared as round or slightly elongated foci with a median size of 2.5 mm [1.5; 3]. Total number, size and prevalence of WMH by lobes and white matter regions were similar between groups, and no interaction with age or sex was found. The number of lesions within the frontal lobe juxtacortical white matter correlated with the age of patients (r = 0.331, p = 0.001) and the duration since migraine onset (r = 0.264, p = 0.012). Patients with different migraine subtypes and without vascular risk factors are characterized by a similar pattern of WMH in the absence of subclinical infarctions or microbleedings. Therefore, WMH have no relevant prognostic value regarding the course of migraine and vascular complications. WMH pattern may be used to differentiate migraine as a primary disorder and other disorders with migraine-like headache and WMH.
Splenic uptake on FDG PET/CT correlates with Kikuchi-Fujimoto disease severity
Authors: Seong Hye , Jeong Yong Hyu , Lee Woon Ji , Kim Jun Hyoung , Kim Jung Ho , Ahn Jin Young , Jeong Su Jin , Choi Jun Yong , Park Yoon Soo , Yeom Joon Sup , Song Young Goo , Cho Arthur , Ku Nam Su
Published: May 2021

Kikuchi-Fujimoto disease (KFD) is usually self-limiting, but prolonged systemic symptoms often result in frequent hospital visits, long admission durations, or missed workdays. We investigated the role of fluorine-18 fluoro-2-deoxy-D-glucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) in assessing KFD severity. We reviewed the records of 31 adult patients with pathologically confirmed KFD who underwent 18F-FDG PET/CT between November 2007 and April 2018 at a tertiary-care referral hospital. Disease severity was assessed using criteria based on clinical manifestations of advanced KFD. Systemic activated lymph nodes and severity of splenic activation were determined using semi-quantitative and volumetric PET/CT parameters. The median of the mean splenic standardized uptake value (SUVmean) was higher in patients with severe KFD than those with mild KFD (2.38 ± 1.18 vs. 1.79 ± 0.99, p = 0.058). Patients with severe KFD had more systemically activated volume and glycolytic activity than those with mild KFD (total lesion glycolysis: 473.5 ± 504.4 vs. 201.6 ± 363.5, p = 0.024). Multivariate logistic regression showed that myalgia (odds ratio [OR] 0.035; 95% confidence interval [CI] 0.001–0.792; p = 0.035), total lymph node SUVmax (cutoff 9.27; OR 24.734; 95% CI 1.323–462.407; p = 0.032), and spleen SUVmean (cutoff 1.79; OR 37.770; 95% CI 1.769–806.583; p = 0.020) were significantly associated with severe KFD. 18F-FDG PET/CT could be useful in assessing KFD severity.