bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mild-to-wild plastic transition is governed by athermal screw dislocation slip in bcc Nb
Authors: Rizzardi Q. , McElfresh C. , Sparks G. , Stauffer D. D. , Marian J. , Maaß R. 
Published: February 2022

AbstractPlastic deformation in crystals is mediated by the motion of line defects known as dislocations. For decades, dislocation activity has been treated as a homogeneous, smooth continuous process. However, it is now recognized that plasticity can be determined by long-range correlated and intermittent collective dislocation processes, known as avalanches. Here we demonstrate in body-centered cubic Nb how the long-range and scale-free dynamics at room temperature are progressively quenched out with decreasing temperature, eventually revealing intermittency with a characteristic length scale that approaches the Burgers vector itself. Plasticity is shown to be bimodal across the studied temperature regime, with conventional thermally-activated smooth plastic flow (‘mild’) coexisting with sporadic bursts (‘wild’) controlled by athermal screw dislocation activity, thereby violating the classical notion of temperature-dependent screw dislocation motion at low temperatures. An abrupt increase of the athermal avalanche component is identified at the critical temperature of the material. Our results indicate that plasticity at any scale can be understood in terms of the coexistence of these mild and wild modes of deformation, which could help design better alloys by suppressing one of the two modes in desired temperature windows.
Embodied neuromorphic intelligence
Authors: Bartolozzi Chiara , Indiveri Giacomo , Donati Elisa 
Published: February 2022

AbstractThe design of robots that interact autonomously with the environment and exhibit complex behaviours is an open challenge that can benefit from understanding what makes living beings fit to act in the world. Neuromorphic engineering studies neural computational principles to develop technologies that can provide a computing substrate for building compact and low-power processing systems. We discuss why endowing robots with neuromorphic technologies – from perception to motor control – represents a promising approach for the creation of robots which can seamlessly integrate in society. We present initial attempts in this direction, highlight open challenges, and propose actions required to overcome current limitations.
Protective immune trajectories in early viral containment of non-pneumonic SARS-CoV-2 infection
Authors: Pekayvaz Kami , Leunig Alexander , Kaiser Rainer , Joppich Markus , Brambs Sophia , Janjic Aleksandar , Popp Oliver , Nixdorf Daniel , Fumagalli Valeria , Schmidt Nora , Polewka Vivien , Anjum Afra , Knottenberg Viktoria , Eivers Luke , Wange Lucas E. , Gold Christoph , Kirchner Marieluise , Muenchhoff Maximilian , Hellmuth Johannes C. , Scherer Clemens , Rubio-Acero Raquel , Eser Tabea , Deák Flora , Puchinger Kerstin , Kuhl Niklas , Linder Andreas , Saar Kathrin , Tomas Lukas , Schulz Christian , Wieser Andreas , Enard Wolfgang , Kroidl Inge , Geldmacher Christof , von Bergwelt-Baildon Michael , Keppler Oliver T. , Munschauer Mathias , Iannacone Matteo , Zimmer Ralf , Mertins Philipp , Hubner Norbert , Hoelscher Michael , Massberg Steffen , Stark Konstantin , Nicolai Leo 
Published: February 2022

AbstractThe antiviral immune response to SARS-CoV-2 infection can limit viral spread and prevent development of pneumonic COVID-19. However, the protective immunological response associated with successful viral containment in the upper airways remains unclear. Here, we combine a multi-omics approach with longitudinal sampling to reveal temporally resolved protective immune signatures in non-pneumonic and ambulatory SARS-CoV-2 infected patients and associate specific immune trajectories with upper airway viral containment. We see a distinct systemic rather than local immune state associated with viral containment, characterized by interferon stimulated gene (ISG) upregulation across circulating immune cell subsets in non-pneumonic SARS-CoV2 infection. We report reduced cytotoxic potential of Natural Killer (NK) and T cells, and an immune-modulatory monocyte phenotype associated with protective immunity in COVID-19. Together, we show protective immune trajectories in SARS-CoV2 infection, which have important implications for patient prognosis and the development of immunomodulatory therapies.
Photo-induced enhancement of lattice fluctuations in metal-halide perovskites
Authors: Wang Mingcong , Gao Yajun , Wang Kai , Liu Jiang , De Wolf Stefaan , Laquai Frédéric 
Published: February 2022

AbstractThe optoelectronic properties of metal-halide perovskites (MHPs) are affected by lattice fluctuations. Using ultrafast pump-probe spectroscopy, we demonstrate that in state-of-the-art mixed-cation MHPs ultrafast photo-induced bandgap narrowing occurs with a linear to super-linear dependence on the excited carrier density ranging from 1017 cm−3 to above 1018 cm−3. Time-domain terahertz spectroscopy reveals carrier localization increases with carrier density. Both observations, the anomalous dependence of the bandgap narrowing and the increased carrier localization can be rationalized by photo-induced lattice fluctuations. The magnitude of the photo-induced lattice fluctuations depends on the intrinsic instability of the MHP lattice. Our findings provide insight into ultrafast processes in MHPs following photoexcitation and thus help to develop a concise picture of the ultrafast photophysics of this important class of emerging semiconductors.
Uncovering interpretable potential confounders in electronic medical records
Authors: Zeng Jiaming , Gensheimer Michael F. , Rubin Daniel L. , Athey Susan , Shachter Ross D. 
Published: February 2022

AbstractRandomized clinical trials (RCT) are the gold standard for informing treatment decisions. Observational studies are often plagued by selection bias, and expert-selected covariates may insufficiently adjust for confounding. We explore how unstructured clinical text can be used to reduce selection bias and improve medical practice. We develop a framework based on natural language processing to uncover interpretable potential confounders from text. We validate our method by comparing the estimated hazard ratio (HR) with and without the confounders against established RCTs. We apply our method to four cohorts built from localized prostate and lung cancer datasets from the Stanford Cancer Institute and show that our method shifts the HR estimate towards the RCT results. The uncovered terms can also be interpreted by oncologists for clinical insights. We present this proof-of-concept study to enable more credible causal inference using observational data, uncover meaningful insights from clinical text, and inform high-stakes medical decisions.
Forecasting the outcome of spintronic experiments with Neural Ordinary Differential Equations
Authors: Chen Xing , Araujo Flavio Abreu , Riou Mathieu , Torrejon Jacob , Ravelosona Dafiné , Kang Wang , Zhao Weisheng , Grollier Julie , Querlioz Damien 
Published: February 2022

AbstractDeep learning has an increasing impact to assist research, allowing, for example, the discovery of novel materials. Until now, however, these artificial intelligence techniques have fallen short of discovering the full differential equation of an experimental physical system. Here we show that a dynamical neural network, trained on a minimal amount of data, can predict the behavior of spintronic devices with high accuracy and an extremely efficient simulation time, compared to the micromagnetic simulations that are usually employed to model them. For this purpose, we re-frame the formalism of Neural Ordinary Differential Equations to the constraints of spintronics: few measured outputs, multiple inputs and internal parameters. We demonstrate with Neural Ordinary Differential Equations an acceleration factor over 200 compared to micromagnetic simulations for a complex problem – the simulation of a reservoir computer made of magnetic skyrmions (20 minutes compared to three days). In a second realization, we show that we can predict the noisy response of experimental spintronic nano-oscillators to varying inputs after training Neural Ordinary Differential Equations on five milliseconds of their measured response to a different set of inputs. Neural Ordinary Differential Equations can therefore constitute a disruptive tool for developing spintronic applications in complement to micromagnetic simulations, which are time-consuming and cannot fit experiments when noise or imperfections are present. Our approach can also be generalized to other electronic devices involving dynamics.
Small Cajal body-associated RNA 2 (scaRNA2) regulates DNA repair pathway choice by inhibiting DNA-PK
Authors: Bergstrand Sofie , O’Brien Eleanor M. , Coucoravas Christos , Hrossova Dominika , Peirasmaki Dimitra , Schmidli Sandro , Dhanjal Soniya , Pederiva Chiara , Siggens Lee , Mortusewicz Oliver , O’Rourke Julienne J. , Farnebo Marianne 
Published: February 2022

AbstractEvidence that long non-coding RNAs (lncRNAs) participate in DNA repair is accumulating, however, whether they can control DNA repair pathway choice is unknown. Here we show that the small Cajal body-specific RNA 2 (scaRNA2) can promote HR by inhibiting DNA-dependent protein kinase (DNA-PK) and, thereby, NHEJ. By binding to the catalytic subunit of DNA-PK (DNA-PKcs), scaRNA2 weakens its interaction with the Ku70/80 subunits, as well as with the LINP1 lncRNA, thereby preventing catalytic activation of the enzyme. Inhibition of DNA-PK by scaRNA2 stimulates DNA end resection by the MRN/CtIP complex, activation of ATM at DNA lesions and subsequent repair by HR. ScaRNA2 is regulated in turn by WRAP53β, which binds this RNA, sequestering it away from DNA-PKcs and allowing NHEJ to proceed. These findings reveal that RNA-dependent control of DNA-PK catalytic activity is involved in regulating whether the cell utilizes NHEJ or HR.
Kindlin-2 haploinsufficiency protects against fatty liver by targeting Foxo1 in mice
Authors: Gao Huanqing , Zhou Liang , Zhong Yiming , Ding Zhen , Lin Sixiong , Hou Xiaoting , Zhou Xiaoqian , Shao Jie , Yang Fan , Zou Xuenong , Cao Huiling , Xiao Guozhi 
Published: February 2022

AbstractNonalcoholic fatty liver disease (NAFLD) affects a large population with incompletely defined mechanism(s). Here we report that Kindlin-2 is dramatically up-regulated in livers in obese mice and patients with NAFLD. Kindlin-2 haploinsufficiency in hepatocytes ameliorates high-fat diet (HFD)-induced NAFLD and glucose intolerance without affecting energy metabolism in mice. In contrast, Kindlin-2 overexpression in liver exacerbates NAFLD and promotes lipid metabolism disorder and inflammation in hepatocytes. A C-terminal region (aa 570-680) of Kindlin-2 binds to and stabilizes Foxo1 by inhibiting its ubiquitination and degradation through the Skp2 E3 ligase. Kindlin-2 deficiency increases Foxo1 phosphorylation at Ser256, which favors its ubiquitination by Skp2. Thus, Kindllin-2 loss down-regulates Foxo1 protein in hepatocytes. Foxo1 overexpression in liver abrogates the ameliorating effect of Kindlin-2 haploinsufficiency on NAFLD in mice. Finally, AAV8-mediated shRNA knockdown of Kindlin-2 in liver alleviates NAFLD in obese mice. Collectively, we demonstrate that Kindlin-2 insufficiency protects against fatty liver by promoting Foxo1 degradation.
The association between the dynamics of COVID-19, related measures, and daytime population in Tokyo
Authors: Yamauchi Takenori , Takeuchi Shouhei , Uchida Mitsuo , Saito Masaya , Kokaze Akatsuki 
Published: February 2022

AbstractIn Japan, a novel coronavirus has been prevalent since January 2020. The Japanese and local governments have implemented various measures, including declaring a state of emergency, according to the epidemic situation in each region. This study estimated the effective reproduction number (Rt) using the number of confirmed positive cases and positivity rates in Tokyo and examined the association between Rt and the rate of increase/decrease in the number of people across 12 sites. In Tokyo, there were five waves in which Rt was persistently estimated as approximately 1.0. The fourth and fifth waves started under the declaration of the state of emergency and coincided with an increase in the number of people. However, the contribution of the number of people to Rt was inconsistent, even when the number of people was of the same magnitude. A possible reason for this is difference in the countermeasures content, as the impact of vaccination was considered to be minor at the time. Where vaccination is insufficient, the wave is terminated by controlling the number of people leaving their homes. It is suggested that infection could be controlled more efficiently, depending on the content of the countermeasures.
Role of endothelial colony forming cells (ECFCs) Tetrahydrobiopterin (BH4) in determining ECFCs functionality in coronary artery disease (CAD) patients
Authors: Sen Atanu , Singh Archna , Roy Ambuj , Mohanty Sujata , Naik Nitish , Kalaivani Mani , Ramakrishnan Lakshmy 
Published: February 2022

AbstractNitric oxide (NO.) is critical for functionality of endothelial colony forming cells (ECFCs). Dimerization of endothelial nitric oxide synthase (eNOS) is must to produce NO. and tetrahydrobiopterin (BH4) plays a crucial role in stabilizing this state. We investigated BH4 level in ECFCs and its effect on ECFCs functionality in CAD patients. Intracellular biopterin levels and ECFCs functionality in terms of cell viability, adhesion, proliferation, in vitro wound healing and angiogenesis were assessed. Guanosine Triphosphate Cyclohydrolase-1 (GTPCH-1) expression was studied in ECFCs. Serum total reactive oxygen/nitrogen species was measured and effect of nitrosative stress on ECFC’s biopterins level and functionality were evaluated by treating with 3-morpholino sydnonimine (SIN-1). BH4 level was significantly lower in ECFCs from CAD patients. Cell proliferation, wound closure reflecting cellular migration as well as in vitro angiogenesis were impaired in ECFCs from CAD patients. Wound healing capacity and angiogenesis were positively correlated with ECFC’s BH4. A negative effect of nitrosative stress on biopterins level and cell functionality was observed in SIN-1 treated ECFCs. ECFCs from CAD exhibited impaired functionality and lower BH4 level. Association of BH4 with wound healing capacity and angiogenesis suggest its role in maintaining ECFC’s functionality. Oxidative stress may be a determinant of intracellular biopterin levels.
Machine Learning analysis of high-grade serous ovarian cancer proteomic dataset reveals novel candidate biomarkers
Authors: Farinella Federica , Merone Mario , Bacco Luca , Capirchio Adriano , Ciccozzi Massimo , Caligiore Daniele 
Published: February 2022

AbstractOvarian cancer is one of the most common gynecological malignancies, ranking third after cervical and uterine cancer. High-grade serous ovarian cancer (HGSOC) is one of the most aggressive subtype, and the late onset of its symptoms leads in most cases to an unfavourable prognosis. Current predictive algorithms used to estimate the risk of having Ovarian Cancer fail to provide sufficient sensitivity and specificity to be used widely in clinical practice. The use of additional biomarkers or parameters such as age or menopausal status to overcome these issues showed only weak improvements. It is necessary to identify novel molecular signatures and the development of new predictive algorithms able to support the diagnosis of HGSOC, and at the same time, deepen the understanding of this elusive disease, with the final goal of improving patient survival. Here, we apply a Machine Learning-based pipeline to an open-source HGSOC Proteomic dataset to develop a decision support system (DSS) that displayed high discerning ability on a dataset of HGSOC biopsies. The proposed DSS consists of a double-step feature selection and a decision tree, with the resulting output consisting of a combination of three highly discriminating proteins: TOP1, PDIA4, and OGN, that could be of interest for further clinical and experimental validation. Furthermore, we took advantage of the ranked list of proteins generated during the feature selection steps to perform a pathway analysis to provide a snapshot of the main deregulated pathways of HGSOC. The datasets used for this study are available in the Clinical Proteomic Tumor Analysis Consortium (CPTAC) data portal (https://cptac-data-portal.georgetown.edu/).
Neuroprotective effect of Mulmina Mango against chemotherapy-induced cognitive decline in mouse model of mammary carcinoma
Authors: John Jeena , Kinra Manas , Ranadive Niraja , Keni Raghuvir , Nayak Pawan Ganesh , Jagdale Rajesh N. , Ahmed Syed M. , Raghavendra Kaggundi V. , Mudgal Jayesh , Nandakumar K. 
Published: February 2022

AbstractThe post-treatment status of breast cancer survivors has become a concern because of the toxicity induced by chemotherapeutic agents in the brain tissues resulting in cognitive deficits, which is generally referred as chemobrain. The aim of this study was to assess the effect of a proprietary ayurvedic formulation Mulmina Mango against chemotherapy-induced cognitive impairment (CICI). Mammary carcinoma was induced by subcutaneously inoculating 4T1 cells into the mammary fat pad of the animals. Intraperitoneal administration of Cyclophosphamide, Methotrexate, 5-Fluorouracil (CMF) regimen was carried out once a week for three weeks. Treatment of Mulmina began one week before chemotherapy and continued till the end of the chemotherapy cycle. After three cycles of chemotherapy, cognitive decline was assessed by Morris water maze task followed by assessment of locomotor activity by open-field test. Tumor progression was evaluated by measurement of tumor volume. Oxidative and neuroinflammatory markers were also evaluated from the isolated brain samples. CMF treatment resulted in a considerable reduction in tumour volume. We found chemotherapy negatively affected behavioral and biochemical parameters in animals and Mulmina treatment ameliorated these cognitive impairments by restoring antioxidant and maintaining cytokine levels. The combination of phytochemicals in Mulmina proved its possible ability to alleviate CICI without affecting chemotherapeutic efficiency and could pave the way for identifying treatment strategies to combat chemobrain.
Diagnosing pleural effusions using mass spectrometry-based multiplexed targeted proteomics quantitating mid- to high-abundance markers of cancer, infection/inflammation and tuberculosis
Authors: Robak Aleksandra , Kistowski Michał , Wojtas Grzegorz , Perzanowska Anna , Targowski Tomasz , Michalak Agata , Krasowski Grzegorz , Dadlez Michał , Domański Dominik 
Published: February 2022

AbstractPleural effusion (PE) is excess fluid in the pleural cavity that stems from lung cancer, other diseases like extra-pulmonary tuberculosis (TB) and pneumonia, or from a variety of benign conditions. Diagnosing its cause is often a clinical challenge and we have applied targeted proteomic methods with the aim of aiding the determination of PE etiology. We developed a mass spectrometry (MS)-based multiple reaction monitoring (MRM)-protein-panel assay to precisely quantitate 53 established cancer-markers, TB-markers, and infection/inflammation-markers currently assessed individually in the clinic, as well as potential biomarkers suggested in the literature for PE classification. Since MS-based proteomic assays are on the cusp of entering clinical use, we assessed the merits of such an approach and this marker panel based on a single-center 209 patient cohort with established etiology. We observed groups of infection/inflammation markers (ADA2, WARS, CXCL10, S100A9, VIM, APCS, LGALS1, CRP, MMP9, and LDHA) that specifically discriminate TB-PEs and other-infectious-PEs, and a number of cancer markers (CDH1, MUC1/CA-15-3, THBS4, MSLN, HPX, SVEP1, SPINT1, CK-18, and CK-8) that discriminate cancerous-PEs. Some previously suggested potential biomarkers did not show any significant difference. Using a Decision Tree/Multiclass classification method, we show a very good discrimination ability for classifying PEs into one of four types: cancerous-PEs (AUC: 0.863), tuberculous-PEs (AUC of 0.859), other-infectious-PEs (AUC of 0.863), and benign-PEs (AUC: 0.842). This type of approach and the indicated markers have the potential to assist in clinical diagnosis in the future, and help with the difficult decision on therapy guidance.
Estimating the potential for global dissemination of pandemic pathogens using the global airline network and healthcare development indices
Authors: Meslé Margaux M. I. , Vivancos Roberto , Hall Ian M. , Christley Robert M. , Leach Steve , Read Jonathan M. 
Published: February 2022

AbstractPandemics have the potential to incur significant health and economic impacts, and can reach a large number of countries from their origin within weeks. Early identification and containment of a newly emerged pandemic within the source country is key for minimising global impact. To identify a country’s potential to control and contain a pathogen with pandemic potential, we compared the quality of a country’s healthcare system against its global airline connectivity. Healthcare development was determined using three multi-factorial indices, while detailed airline passenger data was used to identify the global connectivity of all countries. Proximities of countries to a putative ‘Worst Case Scenario’ (extreme high-connectivity and low-healthcare development) were calculated. We found a positive relationship between a country’s connectivity and healthcare metrics. We also identified countries that potentially pose the greatest risk for pandemic dissemination, notably Dominican Republic, India and Pakistan. China and Mexico, both sources of recent influenza and coronavirus pandemics were also identified as among the highest risk countries. Collectively, lower-middle and upper-middle income countries represented the greatest risk, while high income countries represented the lowest risk. Our analysis represents an alternative approach to identify countries where increased within-country disease surveillance and pandemic preparedness may benefit global health.
Seed quantity affects the fungal community composition detected using metabarcoding
Authors: Oskay Funda , Vettraino Anna Maria , Doğmuş H. Tuğba , Lehtijärvi Asko , Woodward Stephen , Cleary Michelle 
Published: February 2022

AbstractPest introductions via trade in tree seed may result from a lack of adequate survey and validation protocols. Developing better diagnostic protocols to identify potentially harmful pests and pathogens in forest tree seed is of critical importance. High-throughput sequencing-based barcoding and metabarcoding provide effective tools for screening potentially harmful organisms in various plant materials, including seeds. However, the sample size needed to detect the total microorganism diversity of a community is a major challenge in microbiome studies. In this work, we examined how increasing sample size (ranging between 100 and 1000 seeds) influences diversity of fungal communities detected by high throughput sequencing inPinus sylvestrisseeds. Our results showed that as sample size increased, fungal alpha diversity also increased. Beta-diversity estimators detected significant differences between the mycobiota from different samples. However, taxonomic and functional diversity were not correlated with sample size. In addition, we found that increasing the number of PCR replicates resulted in a higher abundance of plant pathogens. We concluded that for the purpose of screening for potentially harmful pathogens using HTS, greater efforts should be made to increase the sample size and replicates when testing tree seed.