bluuebunny/crossref_metadata_2025_split huggingface dataset:
A highly-active, stable and low-cost platinum-free anode catalyst based on RuNi for hydroxide exchange membrane fuel cells
Authors: Xue Yanrong , Shi Lin , Liu Xuerui , Fang Jinjie , Wang Xingdong , Setzler Brian P. , Zhu Wei , Yan Yushan , Zhuang Zhongbin 
Published: November 2020

AbstractThe development of cost-effective hydroxide exchange membrane fuel cells is limited by the lack of high-performance and low-cost anode hydrogen oxidation reaction catalysts. Here we report a Pt-free catalyst Ru7Ni3/C, which exhibits excellent hydrogen oxidation reaction activity in both rotating disk electrode and membrane electrode assembly measurements. The hydrogen oxidation reaction mass activity and specific activity of Ru7Ni3/C, as measured in rotating disk experiments, is about 21 and 25 times that of Pt/C, and 3 and 5 times that of PtRu/C, respectively. The hydroxide exchange membrane fuel cell with Ru7Ni3/C anode can deliver a high peak power density of 2.03 W cm−2 in H2/O2 and 1.23 W cm−2 in H2/air (CO2-free) at 95 °C, surpassing that using PtRu/C anode catalyst, and good durability with less than 5% voltage loss over 100 h of operation. The weakened hydrogen binding of Ru by alloying with Ni and enhanced water adsorption by the presence of surface Ni oxides lead to the high hydrogen oxidation reaction activity of Ru7Ni3/C. By using the Ru7Ni3/C catalyst, the anode cost can be reduced by 85% of the current state-of-the-art PtRu/C, making it highly promising in economical hydroxide exchange membrane fuel cells.
Discovery of multiple anti-CRISPRs highlights anti-defense gene clustering in mobile genetic elements
Authors: Pinilla-Redondo Rafael , Shehreen Saadlee , Marino Nicole D. , Fagerlund Robert D. , Brown Chris M. , Sørensen Søren J. , Fineran Peter C. , Bondy-Denomy Joseph 
Published: November 2020

AbstractMany prokaryotes employ CRISPR–Cas systems to combat invading mobile genetic elements (MGEs). In response, some MGEs have developed strategies to bypass immunity, including anti-CRISPR (Acr) proteins; yet the diversity, distribution and spectrum of activity of this immune evasion strategy remain largely unknown. Here, we report the discovery of new Acrs by assaying candidate genes adjacent to a conserved Acr-associated (Aca) gene, aca5, against a panel of six type I systems: I–F (Pseudomonas, Pectobacterium, and Serratia), I–E (Pseudomonas and Serratia), and I–C (Pseudomonas). We uncover 11 type I–F and/or I–E anti-CRISPR genes encoded on chromosomal and extrachromosomal MGEs within Enterobacteriaceae and Pseudomonas, and an additional Aca (aca9). The acr genes not only associate with other acr genes, but also with genes encoding inhibitors of distinct bacterial defense systems. Thus, our findings highlight the potential exploitation of acr loci neighborhoods for the identification of previously undescribed anti-defense systems.
Injury triggers fascia fibroblast collective cell migration to drive scar formation through N-cadherin
Authors: Jiang Dongsheng , Christ Simon , Correa-Gallegos Donovan , Ramesh Pushkar , Kalgudde Gopal Shruthi , Wannemacher Juliane , Mayr Christoph H. , Lupperger Valerio , Yu Qing , Ye Haifeng , Mück-Häusl Martin , Rajendran Vijayanand , Wan Li , Liu Juan , Mirastschijski Ursula , Volz Thomas , Marr Carsten , Schiller Herbert B. , Rinkevich Yuval 
Published: November 2020

AbstractScars are more severe when the subcutaneous fascia beneath the dermis is injured upon surgical or traumatic wounding. Here, we present a detailed analysis of fascia cell mobilisation by using deep tissue intravital live imaging of acute surgical wounds, fibroblast lineage-specific transgenic mice, and skin-fascia explants (scar-like tissue in a dish – SCAD). We observe that injury triggers a swarming-like collective cell migration of fascia fibroblasts that progressively contracts the skin and form scars. Swarming is exclusive to fascia fibroblasts, and requires the upregulation of N-cadherin. Both swarming and N-cadherin expression are absent from fibroblasts in the upper skin layers and the oral mucosa, tissues that repair wounds with minimal scar. Impeding N-cadherin binding inhibits swarming and skin contraction, and leads to reduced scarring in SCADs and in animals. Fibroblast swarming and N-cadherin thus provide therapeutic avenues to curtail fascia mobilisation and pathological fibrotic responses across a range of medical settings.
Sub-nanoliter metabolomics via mass spectrometry to characterize volume-limited samples
Authors: Li Yafeng , Bouza Marcos , Wu Changsheng , Guo Hengyu , Huang Danning , Doron Gilad , Temenoff Johnna S. , Stecenko Arlene A. , Wang Zhong Lin , Fernández Facundo M. 
Published: November 2020

AbstractThe human metabolome provides a window into the mechanisms and biomarkers of various diseases. However, because of limited availability, many sample types are still difficult to study by metabolomic analyses. Here, we present a mass spectrometry (MS)-based metabolomics strategy that only consumes sub-nanoliter sample volumes. The approach consists of combining a customized metabolomics workflow with a pulsed MS ion generation method, known as triboelectric nanogenerator inductive nanoelectrospray ionization (TENGi nanoESI) MS. Samples tested with this approach include exhaled breath condensate collected from cystic fibrosis patients as well as in vitro-cultured human mesenchymal stromal cells. Both test samples are only available in minimum amounts. Experiments show that picoliter-volume spray pulses suffice to generate high-quality spectral fingerprints, which increase the information density produced per unit sample volume. This TENGi nanoESI strategy has the potential to fill in the gap in metabolomics where liquid chromatography-MS-based analyses cannot be applied. Our method opens up avenues for future investigations into understanding metabolic changes caused by diseases or external stimuli.
Designing accurate emulators for scientific processes using calibration-driven deep models
Authors: Thiagarajan Jayaraman J. , Venkatesh Bindya , Anirudh Rushil , Bremer Peer-Timo , Gaffney Jim , Anderson Gemma , Spears Brian 
Published: November 2020

AbstractPredictive models that accurately emulate complex scientific processes can achieve speed-ups over numerical simulators or experiments and at the same time provide surrogates for improving the subsequent analysis. Consequently, there is a recent surge in utilizing modern machine learning methods to build data-driven emulators. In this work, we study an often overlooked, yet important, problem of choosing loss functions while designing such emulators. Popular choices such as the mean squared error or the mean absolute error are based on a symmetric noise assumption and can be unsuitable for heterogeneous data or asymmetric noise distributions. We propose Learn-by-Calibrating, a novel deep learning approach based on interval calibration for designing emulators that can effectively recover the inherent noise structure without any explicit priors. Using a large suite of use-cases, we demonstrate the efficacy of our approach in providing high-quality emulators, when compared to widely-adopted loss function choices, even in small-data regimes.
Deep learning-enabled multi-organ segmentation in whole-body mouse scans
Authors: Schoppe Oliver , Pan Chenchen , Coronel Javier , Mai Hongcheng , Rong Zhouyi , Todorov Mihail Ivilinov , Müskes Annemarie , Navarro Fernando , Li Hongwei , Ertürk Ali , Menze Bjoern H. 
Published: November 2020

AbstractWhole-body imaging of mice is a key source of information for research. Organ segmentation is a prerequisite for quantitative analysis but is a tedious and error-prone task if done manually. Here, we present a deep learning solution called AIMOS that automatically segments major organs (brain, lungs, heart, liver, kidneys, spleen, bladder, stomach, intestine) and the skeleton in less than a second, orders of magnitude faster than prior algorithms. AIMOS matches or exceeds the segmentation quality of state-of-the-art approaches and of human experts. We exemplify direct applicability for biomedical research for localizing cancer metastases. Furthermore, we show that expert annotations are subject to human error and bias. As a consequence, we show that at least two independently created annotations are needed to assess model performance. Importantly, AIMOS addresses the issue of human bias by identifying the regions where humans are most likely to disagree, and thereby localizes and quantifies this uncertainty for improved downstream analysis. In summary, AIMOS is a powerful open-source tool to increase scalability, reduce bias, and foster reproducibility in many areas of biomedical research.
Climate reverses directionality in the richness–abundance relationship across the World’s main forest biomes
Authors: Madrigal-González Jaime , Calatayud Joaquín , Ballesteros-Cánovas Juan A. , Escudero Adrián , Cayuela Luis , Rueda Marta , Ruiz-Benito Paloma , Herrero Asier , Aponte Cristina , Sagardia Rodrigo , Plumptre Andrew J. , Dupire Sylvain , Espinosa Carlos I. , Tutubalina Olga , Myint Moe , Pataro Luciano , López-Sáez Jerome , Macía Manuel J. , Abegg Meinrad , Zavala Miguel A. , Quesada-Román Adolfo , Vega-Araya Mauricio , Golubeva Elena , Timokhina Yuliya , Stoffel Markus 
Published: November 2020

AbstractMore tree species can increase the carbon storage capacity of forests (here referred to as the more species hypothesis) through increased tree productivity and tree abundance resulting from complementarity, but they can also be the consequence of increased tree abundance through increased available energy (more individuals hypothesis). To test these two contrasting hypotheses, we analyse the most plausible pathways in the richness-abundance relationship and its stability along global climatic gradients. We show that positive effect of species richness on tree abundance only prevails in eight of the twenty-three forest regions considered in this study. In the other forest regions, any benefit from having more species is just as likely (9 regions) or even less likely (6 regions) than the effects of having more individuals. We demonstrate that diversity effects prevail in the most productive environments, and abundance effects become dominant towards the most limiting conditions. These findings can contribute to refining cost-effective mitigation strategies based on fostering carbon storage through increased tree diversity. Specifically, in less productive environments, mitigation measures should promote abundance of locally adapted and stress tolerant tree species instead of increasing species richness.
Skeletal reorganization divergence of N-sulfonyl ynamides
Authors: Zeng Linwei , Lin Yuxin , Li Jiaming , Sajiki Hironao , Xie Hujun , Cui Sunliang 
Published: November 2020

AbstractSkeletal reorganization is a type of intriguing processes because of their interesting mechanism, high atom-economy and synthetic versatility. Herein, we describe an unusual, divergent skeletal reorganization of N-sulfonyl ynamides. Upon treatment with lithium diisopropylamine (LDA), N-sulfonyl ynamides undergo a skeletal reorganization to deliver thiete sulfones, while the additional use of 1,3-dimethyl-tetrahydropyrimidin-2(1H)-one (DMPU) shifts the process to furnish propargyl sulfonamides. This skeletal reorganization divergence features broad substrate scope and scalability. Mechanistically, experimental and computational studies reveal that these processes may initiate from a lithiation/4-exo-dig cyclization cascade, and the following ligand-dependent 1,3-sulfonyl migration or β-elimination would control the chemodivergence. This protocol additionally provides a facile access to a variety of privileged molecules from easily accessible ynamides.
The nuclear pore primes recombination-dependent DNA synthesis at arrested forks by promoting SUMO removal
Authors: Kramarz Karol , Schirmeisen Kamila , Boucherit Virginie , Ait Saada Anissia , Lovo Claire , Palancade Benoit , Freudenreich Catherine , Lambert Sarah A. E. 
Published: November 2020

AbstractNuclear Pore complexes (NPCs) act as docking sites to anchor particular DNA lesions facilitating DNA repair by elusive mechanisms. Using replication fork barriers in fission yeast, we report that relocation of arrested forks to NPCs occurred after Rad51 loading and its enzymatic activity. The E3 SUMO ligase Pli1 acts at arrested forks to safeguard integrity of nascent strands and generates poly-SUMOylation which promote relocation to NPCs but impede the resumption of DNA synthesis by homologous recombination (HR). Anchorage to NPCs allows SUMO removal by the SENP SUMO protease Ulp1 and the proteasome, promoting timely resumption of DNA synthesis. Preventing Pli1-mediated SUMO chains was sufficient to bypass the need for anchorage to NPCs and the inhibitory effect of poly-SUMOylation on HR-mediated DNA synthesis. Our work establishes a novel spatial control of Recombination-Dependent Replication (RDR) at a unique sequence that is distinct from mechanisms engaged at collapsed-forks and breaks within repeated sequences.
Machine learning property prediction for organic photovoltaic devices
Authors: Meftahi Nastaran , Klymenko Mykhailo , Christofferson Andrew J. , Bach Udo , Winkler David A. , Russo Salvy P. 
Published: November 2020

AbstractOrganic photovoltaic (OPV) materials are promising candidates for cheap, printable solar cells. However, there are a very large number of potential donors and acceptors, making selection of the best materials difficult. Here, we show that machine-learning approaches can leverage computationally expensive DFT calculations to estimate important OPV materials properties quickly and accurately. We generate quantitative relationships between simple and interpretable chemical signature and one-hot descriptors and OPV power conversion efficiency (PCE), open circuit potential (Voc), short circuit density (Jsc), highest occupied molecular orbital (HOMO) energy, lowest unoccupied molecular orbital (LUMO) energy, and the HOMO–LUMO gap. The most robust and predictive models could predict PCE (computed by DFT) with a standard error of ±0.5 for percentage PCE for both the training and test set. This model is useful for pre-screening potential donor and acceptor materials for OPV applications, accelerating design of these devices for green energy applications.
Predominance of non-adiabatic effects in zero-point renormalization of the electronic band gap
Authors: Miglio Anna , Brousseau-Couture Véronique , Godbout Emile , Antonius Gabriel , Chan Yang-Hao , Louie Steven G. , Côté Michel , Giantomassi Matteo , Gonze Xavier 
Published: November 2020

AbstractElectronic and optical properties of materials are affected by atomic motion through the electron–phonon interaction: not only band gaps change with temperature, but even at absolute zero temperature, zero-point motion causes band-gap renormalization. We present a large-scale first-principles evaluation of the zero-point renormalization of band edges beyond the adiabatic approximation. For materials with light elements, the band gap renormalization is often larger than 0.3 eV, and up to 0.7 eV. This effect cannot be ignored if accurate band gaps are sought. For infrared-active materials, global agreement with available experimental data is obtained only when non-adiabatic effects are taken into account. They even dominate zero-point renormalization for many materials, as shown by a generalized Fröhlich model that includes multiple phonon branches, anisotropic and degenerate electronic extrema, whose range of validity is established by comparison with first-principles results.
ClimActor, harmonized transnational data on climate network participation by city and regional governments
Authors: Hsu Angel , Yeo Zhi Yi , Rauber Ross , Sun James , Kim Yunsoo , Raghavan Sowmya , Chin Nicholas , Namdeo Vasu , Weinfurter Amy 
Published: November 2020

AbstractCities and regions have become increasingly engaged in global climate change governance. They are pledging their own climate mitigation targets and participating in membership networks that typically are transnational in nature and engage thousands of subnational governments. Researching these growing trends in participation has been difficult due to the disparate and inconsistent nature of this self-reported data. To facilitate future analyses of these actors, we introduce ClimActor, the largest harmonized global dataset of more than 10,000 city and regional governments participating in networks like the Global Covenant of Mayors for Climate and Energy, C40 Cities for Climate Leadership, ICLEI Local Leaders for Sustainability, among others. We include key contextual information on each actor’s population, geographic location, and administrative jurisdiction to facilitate disambiguation of potential overlaps in actions or emissions. We also provide a series of cleaning functions based on phonetic and fuzzy string matching algorithms within an open-source R package to make it easy for anyone to immediately use the ClimActor dataset with other relevant data.
Improved classification of rheumatoid arthritis with a score including anti-acetylated ornithine antibodies
Authors: Rodriguez-Martínez Lorena , Bang Holger , Regueiro Cristina , Nuño Laura , Triguero-Martinez Ana , Peiteado Diana , Ortiz Ana M. , Villalba Alejandro , Martinez-Feito Ana , Balsa Alejandro , Gonzalez-Alvaro Isidoro , Gonzalez Antonio 
Published: November 2020

AbstractThe presence of rheumatoid factor (RF) or anti-cyclic citrullinated peptide (anti-CCP) autoantibodies contributes to the current rheumatoid arthritis (RA) classification criteria. These criteria involve stratification on antibody levels, which limits reproducibility, and underperform in the RA patients without RF and anti-CCP. Here, we have explored if two anti-acetylated peptide antibodies (AAPA), anti-acetylated lysine (AcLys) and anti-acetylated ornithine (AcOrn), could improve the performance of the current criteria. The analysis was done in 1062 prospectively-followed early arthritis (EA) patients. The anti-AcOrn were more informative than the anti-AcLys, the conventional RA antibodies and the anti-carbamylated protein antibodies. The anti-AcOrn produced a classification that did not require antibody levels and showed improved specificity (77.6% vs. 72.6%, p = 0.003) and accuracy (79.0% vs. 75.8%, p = 0.002) over the current criteria. These improvements were obtained with a scoring system that values concordance between anti-AcOrn, RF and anti-CCP. No significant gain was obtained in sensitivity (80.2% vs. 78.8%, p = 0.25) or in improving the classification of the RA patients lacking RF and anti-CCP, although the anti-AcOrn ranked first among the analysed new antibodies. Therefore, the anti-AcOrn antibodies could contribute to the improvement of RA classification criteria by exploiting antibody concordance.
Determinants of length of stay after cesarean sections in the Friuli Venezia Giulia Region (North-Eastern Italy), 2005–2015
Authors: Cegolon L. , Mastrangelo G. , Maso G. , Pozzo G. Dal , Heymann W. C. , Ronfani L. , Barbone F. 
Published: November 2020

AbstractSince Italy has the highest cesarean section (CS) rate (38.1%) among all European countries, the containment of health care costs associated with CS is needed, along with control of length of hospital stay (LOS) following CS. This population based cross-sectional study aims to investigate LoS post CS (overall CS, OCS; planned CS, PCS; urgent/emergency CS, UCS), in Friuli Venezia Giulia (a region of North-Eastern Italy) during 2005–2015, adjusting for a considerable number factors, including various obstetric conditions/complications. Maternal and newborn characteristics (health care setting and timeframe; maternal health factors; child’s size factors; child’s fragility factors; socio-demographic background; obstetric history; obstetric conditions) were used as independent variables. LoS (post OCS, PCS, UCS) was the outcome measure. The statistical analysis was conducted with multivariable linear (LoS expressed as adjusted mean, in days) as well as logistic (adjusted proportion of LoS > 4 days vs. LoS ≤ 4 days, using a 4 day cutoff for early discharge, ED) regression. An important decreasing trend over time in mean LoS and LoS > ED was observed for both PCS and UCS. LoS post CS was shorter with parity and history of CS, whereas it was longer among non-EU mothers. Several obstetric conditions/complications were associated with extended LoS. Whilst eclampsia/pre-eclampsia and preterm gestations (33–36 weeks) were predominantly associated with longer LoS post UCS, for PCS LoS was significantly longer with birthweight 2.0–2.5 kg, multiple birth and increasing maternal age. Strong significant inter-hospital variation remained after adjustment for the major clinical conditions. This study shows that routinely collected administrative data provide useful information for health planning and monitoring, identifying inter-hospital differences that could be targeted by policy interventions aimed at improving the efficiency of obstetric care. The important decreasing trend over time of LoS post CS, coupled with the impact of some socio-demographic and obstetric history factors on LoS, seemingly suggests a positive approach of health care providers of FVG in decision making on hospitalization length post CS. However, the significant role of several obstetric conditions did not influence hospital variation. Inter-hospital variations of LoS could depend on a number of factors, including the capacity to discharge patients into the surrounding non-acute facilities. Further studies are warranted to ascertain whether LoS can be attributed to hospital efficiency rather than the characteristics of the hospital catchment area.
Activation of toll like receptor 4 (TLR4) promotes cardiomyocyte apoptosis through SIRT2 dependent p53 deacetylation
Authors: Katare Parmeshwar Bajirao , Nizami Hina Lateef , Paramesha Bugga , Dinda Amit K. , Banerjee Sanjay K. 
Published: November 2020

AbstractCardiomyocyte inflammation followed by apoptosis and fibrosis is an important mediator for development and progression of heart failure. Activation of toll-like receptor 4 (TLR4), an important regulator of inflammation, causes the progression of cardiac hypertrophy and injury. However, the precise mechanism of TLR4-mediated adverse cardiac outcomes is still elusive. The present study was designed to find the role of TLR4 in cardiac fibrosis and apoptosis, and molecular mechanism thereof. Rats were treated with TLR4 agonist (LPS 12.5 μg/kg/day) through osmotic pump for 14 days. To simulate the condition in vitro, H9c2 cells were treated with LPS (1 μg/ml). Similarly, H9c2 cells were transfected with TLR4 and SIRT2 c-DNA clone for overexpression. Myocardial oxidative stress, inflammation, fibrosis and mitochondrial parameters were evaluated both in vitro and in vivo. Cardiac inflammation after LPS treatment was confirmed by increased TNF-α and IL-6 expression in rat heart. There was a marked increase in oxidative stress as observed by increased TBARS and decreased endogenous antioxidants (GSH and catalase), along with mitochondrial dysfunction as measured by mitochondrial complex activity in LPS-treated rat hearts. Histopathological examination showed the presence of cardiac fibrosis after LPS treatment. Protein expression of nuclear p53 and cleaved caspase-7/caspase-9 was significantly increased in LPS treated heart. Similar to in vivo study, nuclear translocation of p53, mitochondrial dysfunction and cellular apoptosis were observed in H9c2 cells treated with LPS. Our data also indicate that decreased expression of SIRT2 was associated with increased acetylation of p53 after LPS treatment. In conclusion, TLR4 activation in rats promotes cardiac inflammation, mitochondrial dysfunction, apoptosis and fibrosis. p53 and caspase 7/caspase 9 were found to play an important role in TLR4-mediated apoptosis. Our data suggest that, reducing TLR4 mediated fibrosis and apoptosis could be a novel approach in the treatment of heart failure, keeping in the view the major role played by TLR4 in cardiac inflammation.