bluuebunny/crossref_metadata_2025_split huggingface dataset:
Spatial interplay of lymphocytes and fibroblasts in estrogen receptor-positive HER2-negative breast cancer
Authors: Nederlof I. , Hajizadeh S. , Sobhani F. , Raza S. E. A. , AbdulJabbar K. , Harkes R. , van de Vijver M. J. , Salgado R. , Desmedt C. , Kok M. , Yuan Y. , Horlings H. M. 
Published: April 2022

AbstractIn estrogen-receptor-positive, HER2-negative (ER+HER2−) breast cancer, higher levels of tumor infiltrating lymphocytes (TILs) are often associated with a poor prognosis and this phenomenon is still poorly understood. Fibroblasts represent one of the most frequent cells in breast cancer and harbor immunomodulatory capabilities. Here, we evaluate the molecular and clinical impact of the spatial patterns of TILs and fibroblast in ER+HER2− breast cancer. We used a deep neural network to locate and identify tumor, TILs, and fibroblasts on hematoxylin and eosin-stained slides from 179 ER+HER2− breast tumors (ICGC cohort) together with a new density estimation analysis to measure the spatial patterns. We clustered tumors based on their spatial patterns and gene set enrichment analysis was performed to study their molecular characteristics. We independently assessed the spatial patterns in a second cohort of ER+HER2− breast cancer (N = 630, METABRIC) and studied their prognostic value. The spatial integration of fibroblasts, TILs, and tumor cells leads to a new reproducible spatial classification of ER+HER2− breast cancer and is linked to inflammation, fibroblast meddling, or immunosuppression. ER+HER2− patients with high TIL did not have a significant improved overall survival (HR = 0.76, P = 0.212), except when they had received chemotherapy (HR = 0.447). A poorer survival was observed for patients with high fibroblasts that did not show a high level of TILs (HR = 1.661, P = 0.0303). Especially spatial mixing of fibroblasts and TILs was associated with a good prognosis (HR = 0.464, P = 0.013). Our findings demonstrate a reproducible pipeline for the spatial profiling of TILs and fibroblasts in ER+HER2− breast cancer and suggest that this spatial interplay holds a decisive role in their cancer-immune interactions.
Is conservative management of ductal carcinoma in situ risky?
Authors: Zheng Lan , Gökmen-Polar Yesim , Badve Sunil S. 
Published: April 2022

AbstractNonsurgical management of ductal carcinoma in situ is controversial and little is known about the long-term consequences of this approach. In this study, we aimed to determine the risk of (a) upstaging to invasive carcinoma at excision and (b) ipsilateral breast cancer events in patients who might have been eligible for nonsurgical management of DCIS trials. Data from women aged 20 years or older with a biopsy diagnosis of DCIS between January 1, 2010 to December 31, 2014 were collated. The women underwent biopsy and surgical resection (lumpectomy or mastectomy) and were treated with radiation or endocrine therapy as per treating physicians’ choice. The development of ipsilateral breast cancer events (IBEs) was analyzed in patients with at least 5 years of follow-up after standard of care therapy for DCIS. Subset-analysis was undertaken to identify the incidence of IBEs in patients eligible for nonsurgical management trials. The study population consisted of 378 patients with matched cases of biopsy and surgical excision. The overall upstaging rate to IBC was 14.3 and 12.9% for COMET, 8.8% for LORIS, and 10.7% for LORD trial “eligible” patients. At 5 years of follow-up, ~11.5% of overall and trial eligible patients developed IBEs of which approximately half were invasive IBEs. In conclusion, women with DCIS who would have been eligible for nonsurgical management trials have a significantly high risk of developing ipsilateral breast events within 5 years of diagnosis. Better selection criteria are needed to identify DCIS patients who are at very low risk for the development of IBC.
Discovering plasticity models without stress data
Authors: Flaschel Moritz , Kumar Siddhant , De Lorenzis Laura 
Published: April 2022

AbstractWe propose an approach for data-driven automated discovery of material laws, which we call EUCLID (Efficient Unsupervised Constitutive Law Identification and Discovery), and we apply it here to the discovery of plasticity models, including arbitrarily shaped yield surfaces and isotropic and/or kinematic hardening laws. The approach isunsupervised, i.e., it requires no stress data but only full-field displacement and global force data; it deliversinterpretablemodels, i.e., models that are embodied by parsimonious mathematical expressions discovered through sparse regression of a potentially large catalog of candidate functions; it isone-shot, i.e., discovery only needs one experiment. The material model library is constructed by expanding the yield function with a Fourier series, whereas isotropic and kinematic hardening is introduced by assuming a yield function dependency on internal history variables that evolve with the plastic deformation. For selecting the most relevant Fourier modes and identifying the hardening behavior, EUCLID employs physics knowledge, i.e., the optimization problem that governs the discovery enforces the equilibrium constraints in the bulk and at the loaded boundary of the domain. Sparsity promoting regularization is deployed to generate a set of solutions out of which a solution with low cost and high parsimony is automatically selected. Through virtual experiments, we demonstrate the ability of EUCLID to accurately discover several plastic yield surfaces and hardening mechanisms of different complexity.
Delocalization of dark and bright excitons in flat-band materials and the optical properties of V2O5
Authors: Gorelov Vitaly , Reining Lucia , Feneberg Martin , Goldhahn Rüdiger , Schleife André , Lambrecht Walter R. L. , Gatti Matteo 
Published: April 2022

AbstractThe simplest picture of excitons in materials with atomic-like localization of electrons is that of Frenkel excitons, where electrons and holes stay close together, which is associated with a large binding energy. Here, using the example of the layered oxide V2O5, we show how localized charge-transfer excitations combine to form excitons that also have a huge binding energy but, at the same time, a large electron-hole distance, and we explain this seemingly contradictory finding. The anisotropy of the exciton delocalization is determined by the local anisotropy of the structure, whereas the exciton extends orthogonally to the chains formed by the crystal structure. Moreover, we show that the bright exciton goes together with a dark exciton of even larger binding energy and more pronounced anisotropy. These findings are obtained by combining first principles many-body perturbation theory calculations, ellipsometry experiments, and tight binding modelling, leading to very good agreement and a consistent picture. Our explanation is general and can be extended to other materials.
Modeling and simulation of microstructure in metallic systems based on multi-physics approaches
Authors: Mianroodi Jaber Rezaei , Shanthraj Pratheek , Liu Chuanlai , Vakili Samad , Roongta Sharan , Siboni Nima Hamidi , Perchikov Nathan , Bai Yang , Svendsen Bob , Roters Franz , Raabe Dierk , Diehl Martin 
Published: April 2022

AbstractThe complex interplay between chemistry, microstructure, and behavior of many engineering materials has been investigated predominantly by experimental methods. Parallel to the increase in computer power, advances in computational modeling methods have resulted in a level of sophistication which is comparable to that of experiments. At the continuum level, one class of such models is based on continuum thermodynamics, phase-field methods, and crystal plasticity, facilitating the account of multiple physical mechanisms (multi-physics) and their interaction during microstructure evolution. This paper reviews the status of simulation approaches and software packages in this field and gives an outlook towards promising research directions.
A deep learned nanowire segmentation model using synthetic data augmentation
Authors: Lin Binbin , Emami Nima , Santos David A. , Luo Yuting , Banerjee Sarbajit , Xu Bai-Xiang 
Published: April 2022

AbstractAutomated particle segmentation and feature analysis of experimental image data are indispensable for data-driven material science. Deep learning-based image segmentation algorithms are promising techniques to achieve this goal but are challenging to use due to the acquisition of a large number of training images. In the present work, synthetic images are applied, resembling the experimental images in terms of geometrical and visual features, to train the state-of-art Mask region-based convolutional neural networks to segment vanadium pentoxide nanowires, a cathode material within optical density-based images acquired using spectromicroscopy. The results demonstrate the instance segmentation power in real optical intensity-based spectromicroscopy images of complex nanowires in overlapped networks and provide reliable statistical information. The model can further be used to segment nanowires in scanning electron microscopy images, which are fundamentally different from the training dataset known to the model. The proposed methodology can be extended to any optical intensity-based images of variable particle morphology, material class, and beyond.
Nucleosome footprinting in plasma cell-free DNA for the pre-surgical diagnosis of ovarian cancer
Authors: Vanderstichele Adriaan , Busschaert Pieter , Landolfo Chiara , Olbrecht Siel , Coosemans An , Froyman Wouter , Loverix Liselore , Concin Nicole , Braicu Elena Ioana , Wimberger Pauline , Van Nieuwenhuysen Els , Han Sileny N. , Van Gorp Toon , Venken Tom , Heremans Ruben , Neven Patrick , Bourne Tom , Van Calster Ben , Timmerman Dirk , Lambrechts Diether , Vergote Ignace 
Published: April 2022

AbstractFragmentation patterns of plasma cell-free DNA (cfDNA) are known to reflect nucleosome positions of cell types contributing to cfDNA. Based on cfDNA fragmentation patterns, the deviation in nucleosome footprints was quantified between diagnosed ovarian cancer patients and healthy individuals. Multinomial modeling was subsequently applied to capture these deviations in a per sample nucleosome footprint score. Validation was performed in 271 cfDNAs pre-surgically collected from women with an adnexal mass. We confirmed that nucleosome scores were elevated in invasive carcinoma patients, but not in patients with benign or borderline disease. Combining nucleosome scores with chromosomal instability scores assessed in the same cfDNA improved prediction of malignancy. Nucleosome scores were, however, more reliable to predict non-high-grade serous ovarian tumors, which are characterized by low chromosomal instability. These data highlight that compared to chromosomal instability, nucleosome footprinting provides a complementary and more generic read-out for pre-surgical diagnosis of invasive disease in women with adnexal masses.
The effect of bubble nucleation on the performance of a wickless heat pipe in microgravity
Authors: Yu Jiaheng , Pawar Anisha , Plawsky Joel L. , Chao David F. 
Published: April 2022

AbstractBubble nucleation was investigated in a 20-mm-long, wickless heat pipe on the International Space Station. Over 20 h of running experiments using pentane as the working fluid, more than 100 nucleation events were observed. Bubble nucleation at the heater end temporarily boosted peak pressures and vapor temperatures in the device. At the moment of nucleation, the heater wall temperature significantly decreased due to increased evaporation and the original vapor bubble collapsed due to increased pressure. A thermal model was developed and using the measured temperatures and pressures, heat transfer coefficients near the heater end of the system were extracted. Peak heat transfer coefficients during the nucleation event were over a factor of three higher than at steady-state. The heat transfer coefficient data were all collapsed in the form of a single, linear correlation relating the Nusselt number to the Ohnesorge number.
An ultralight, flexible, and biocompatible all-fiber motion sensor for artificial intelligence wearable electronics
Authors: Lin Sen , Hu Shuang , Song Wei , Gu Miaoqing , Liu Junchen , Song Jianan , Liu Zhenglian , Li Ziwei , Huang Kun , Wu Yufeng , Lei Ming , Wu Hui 
Published: April 2022

AbstractNew-generation human body motion sensors for wearable electronics and intelligent medicine are required to comply with stringent requirements in terms of ultralight weight, flexibility, stability, biocompatibility, and extreme precision. However, conventional sensors are hard to fulfill all these criteria due to their rigid structure, high-density sensing materials used as the constituents, as well as hermetical and compact assembly strategy. Here, we report an ultralight sensing material based on radial anisotropic porous silver fiber (RAPSF), which has been manufactured by phase separation and temperature-controlled grain growth strategy on a modified blow-spinning system. The resistance of RAPSF could be dynamically adjusted depending on the deflected shape. Furthermore, an all-fiber motion sensor (AFMS) with an ultra-low density of 68.70 mg cm−3and an overall weigh of 7.95 mg was fabricated via layer-by-layer assembly. The sensor exhibited outstanding flexibility, breathability, biocompatibility, and remarkable body motion recognition ability. Moreover, the AFMS was shown to have great potential as an artificial intelligence throat sensor for throat state identification at the accuracy above 85%, allowing one to spot the early onset of the viral throat illness.
Coherence of a charge stabilised tin-vacancy spin in diamond
Authors: Görlitz Johannes , Herrmann Dennis , Fuchs Philipp , Iwasaki Takayuki , Taniguchi Takashi , Rogalla Detlef , Hardeman David , Colard Pierre-Olivier , Markham Matthew , Hatano Mutsuko , Becher Christoph 
Published: April 2022

AbstractQuantum information processing (QIP) with solid state spin qubits strongly depends on the efficient initialisation of the qubit’s desired charge state. While the negatively charged tin-vacancy (SnV−) centre in diamond has emerged as an excellent platform for realising QIP protocols due to long spin coherence times at liquid helium temperature and lifetime limited optical transitions, its usefulness is severely limited by termination of the fluorescence under resonant excitation. Here, we unveil the underlying charge cycle, potentially applicable to all group IV-vacancy (G4V) centres, and exploit it to demonstrate highly efficient and rapid initialisation of the desired negative charge state of single SnV centres while preserving long term stable optical resonances. In addition to investigating the optical coherence, we all-optically probe the coherence of the ground state spins by means of coherent population trapping and find a spin dephasing time of 5(1) μs. Furthermore, we demonstrate proof-of-principle single shot spin state readout without the necessity of a magnetic field aligned to the symmetry axis of the defect.
Quantum process tomography on holographic metasurfaces
Authors: Wu Qing-Yuan , Meng Zhe , Yang Jia-Zhi , Zhang An-Ning 
Published: April 2022

AbstractHolographic metasurfaces and their applications have garnered significant attention owing to their role in polarization control. In this study, we demonstrate that the quantum properties of holographic metasurfaces can be obtained by quantum state tomography (QST) and quantum process tomography (QPT). We perform QST to obtain the experimental output states by extracting information from holograms encoded on the holographic metasurface, and develop a QPT-based method to estimate the quantum process of the metasurface. The theoretical output states derived from the estimated quantum process are in good agreement with the experimental output states, proving the effectiveness of our method. Our work not only provides theoretical and experimental analysis for understanding the quantum properties of holographic metasurfaces, but also paves the way for the application of holographic metasurfaces in quantum field.
Empirical evidence for recent global shifts in vegetation resilience
Authors: Smith Taylor , Traxl Dominik , Boers Niklas 
Published: April 2022

AbstractThe character and health of ecosystems worldwide is tightly coupled to changes in Earth’s climate. Theory suggests that ecosystem resilience—the ability of ecosystems to resist and recover from external shocks such as droughts and fires—can be inferred from their natural variability. Here, we quantify vegetation resilience globally with complementary metrics based on two independent long-term satellite records. We first empirically confirm that the recovery rates from large perturbations can be closely approximated from internal vegetation variability across vegetation types and climate zones. On the basis of this empirical relationship, we quantify vegetation resilience continuously and globally from 1992 to 2017. Long-term vegetation resilience trends are spatially heterogeneous, with overall increasing resilience in the tropics and decreasing resilience at higher latitudes. Shorter-term trends, however, reveal a marked shift towards a global decline in vegetation resilience since the early 2000s, particularly in the equatorial rainforest belt.
A European-wide dataset to uncover adaptive traits of Listeria monocytogenes to diverse ecological niches
Authors: Félix Benjamin , Sevellec Yann , Palma Federica , Douarre Pierre Emmanuel , Felten Arnaud , Radomski Nicolas , Mallet Ludovic , Blanchard Yannick , Leroux Aurélie , Soumet Christophe , Bridier Arnaud , Piveteau Pascal , Ascensio Eliette , Hébraud Michel , Karpíšková Renáta , Gelbíčová Tereza , Torresi Marina , Pomilio Francesco , Cammà Cesare , Di Pasquale Adriano , Skjerdal Taran , Pietzka Ariane , Ruppitsch Werner , Canelhas Monica Ricão , Papić Bojan , Hurtado Ana , Wullings Bart , Bulawova Hana , Castro Hanna , Lindström Miia , Korkeala Hannu , Šteingolde Žanete , Kramarenko Toomas , Cabanova Lenka , Szymczak Barbara , Gareis Manfred , Oswaldi Verena , Marti Elisabet , Seyfarth Anne-Mette , Leblanc Jean-Charles , Guillier Laurent , Roussel Sophie 
Published: April 2022

AbstractListeria monocytogenes (Lm) is a ubiquitous bacterium that causes listeriosis, a serious foodborne illness. In the nature-to-human transmission route, Lm can prosper in various ecological niches. Soil and decaying organic matter are its primary reservoirs. Certain clonal complexes (CCs) are over-represented in food production and represent a challenge to food safety. To gain new understanding of Lm adaptation mechanisms in food, the genetic background of strains found in animals and environment should be investigated in comparison to that of food strains. Twenty-one partners, including food, environment, veterinary and public health laboratories, constructed a dataset of 1484 genomes originating from Lm strains collected in 19 European countries. This dataset encompasses a large number of CCs occurring worldwide, covers many diverse habitats and is balanced between ecological compartments and geographic regions. The dataset presented here will contribute to improve our understanding of Lm ecology and should aid in the surveillance of Lm. This dataset provides a basis for the discovery of the genetic traits underlying Lm adaptation to different ecological niches.
Dental pulp stem cells as a therapy for congenital entero-neuropathy
Authors: Yoshimaru Koichiro , Yamaza Takayoshi , Kajioka Shunichi , Sonoda Soichiro , Yanagi Yusuke , Matsuura Toshiharu , Yoshizumi Junko , Oda Yoshinao , Iwata Naoko , Takai Chiho , Nakayama Shinsuke , Taguchi Tomoaki 
Published: April 2022

AbstractHirschsprung’s disease is a congenital entero-neuropathy that causes chronic constipation and intestinal obstruction. New treatments for entero-neuropathy are needed because current surgical strategies have limitations5. Entero-neuropathy results from enteric nervous system dysfunction due to incomplete colonization of the distal intestine by neural crest-derived cells. Impaired cooperation between the enteric nervous system and intestinal pacemaker cells may also contribute to entero-neuropathy. Stem cell therapy to repair these multiple defects represents a novel treatment approach. Dental pulp stem cells derived from deciduous teeth (dDPSCs) are multipotent cranial neural crest-derived cells, but it remains unknown whether dDPSCs have potential as a new therapy for entero-neuropathy. Here we show that intravenous transplantation of dDPSCs into the Japanese Fancy-1 mouse, an established model of hypoganglionosis and entero-neuropathy, improves large intestinal structure and function and prolongs survival. Intravenously injected dDPSCs migrate to affected regions of the intestine through interactions between stromal cell-derived factor-1α and C-X-C chemokine receptor type-4. Transplanted dDPSCs differentiate into both pacemaker cells and enteric neurons in the proximal colon to improve electrical and peristaltic activity, in addition to their paracrine effects. Our findings indicate that transplanted dDPSCs can differentiate into different cell types to correct entero-neuropathy-associated defects.
Non-melancholic depressive symptoms are associated with above average fat mass index in the Helsinki birth cohort study
Authors: Eriksson Mia D. , Eriksson Johan G. , Korhonen Päivi , Salonen Minna K. , Mikkola Tuija M. , Kajantie Eero , Wasenius Niko S. , von Bonsdorff Mikaela , Kautiainen Hannu , Laine Merja K. 
Published: April 2022

AbstractThere is an existing link between two of the most common diseases, obesity and depression. These are both of great public health concern, but little is known about the relationships between the subtypes of these conditions. We hypothesized that non-melancholic depressive symptoms have a stronger relationship with both body composition (lean mass and fat mass) and dysfunctional glucose metabolism than melancholic depression. For this cross-sectional study 1510 participants from the Helsinki Birth Cohort Study had their body composition evaluated as lean mass and fat mass (Lean Mass Index [LMI, kg/m2] + Fat Mass Index [FMI kg/m2] = Body Mass Index). Participants were evaluated for depressive symptoms utilizing the Beck depression inventory, and had laboratory assessments including an oral glucose tolerance test. Higher than average FMI was associated with a higher percentage (mean [%], 95% CI) of participants scoring in the depressive range of the Beck depression inventory (20.2, 17.2–23.2) compared to those with low FMI (16.3, 13.8–18.9; p = 0.048) when adjusted for age, sex, education, and fasting plasma glucose concentration. Higher FMI was associated with a higher likelihood of having depressive symptoms (OR per 1-SD FMI = 1.37, 95% CI 1.13–1.65), whereas higher LMI was associated with a lower likelihood of having depressive symptoms (OR per 1-SD LMI = 0.76, 95% CI 0.64–0.91). Participants with an above average FMI more frequently (mean [%], 95% CI) had non-melancholic depressive symptoms (14.7, 11.8–17.7) as compared to those with low FMI (9.7, 7.6–11.9; p = 0.008) regardless of LMI levels. There was no difference between the body composition groups in the likelihood of having melancholic depressive symptoms. The non-melancholic group had higher (mean [kg/m2], SD) FMI (9.6, 4.1) than either of the other groups (BDI < 10: 7.7, 3.1; melancholic: 7.9, 3.6; p < 0.001), and a higher (mean [mmol/l], SD) 2-h glucose concentration (7.21, 1.65) than the non-depressed group (6.71, 1.70; p = 0.005). As hypothesized, non-melancholic depressive symptoms are most closely related to high fat mass index and dysfunctional glucose metabolism.