bluuebunny/crossref_metadata_2025_split huggingface dataset:
Single-cell long noncoding RNA (lncRNA) transcriptome implicates MALAT1 in triple-negative breast cancer (TNBC) resistance to neoadjuvant chemotherapy
Authors: Shaath Hibah , Vishnubalaji Radhakrishnan , Elango Ramesh , Khattak Shahryar , Alajez Nehad M. 
Published: January 2021

AbstractCumulative evidence suggests added benefit for neoadjuvant chemotherapy (NAC) in a subset of triple-negative breast cancer (TNBC) patients. Herein we identified the long noncoding RNA (lncRNA) transcriptional landscape associated with TNBC resistance to NAC, employing 1758 single cells from three extinction and three persistence TNBC patients. Using Iterative Clustering and Guide-gene Selection (ICGS) and uniform manifold approximation and projection (UMAP) dimensionality reduction analysis, we observed single cells derived from each patient to largely cluster together. Comparing the lncRNA transcriptome from single cells through the course of NAC treatment revealed minimal overlap based on lncRNA transcriptome, suggesting substantial effects of NAC on lncRNA transcription. The differential analysis revealed upregulation of 202 and downregulation of 19 lncRNAs in the persistence group, including upregulation of five different transcripts encoding for the MALAT1 lncRNA. CRISPR/Cas9-mediated MALAT1 promoter deletion in BT-549 TNBC model enhanced sensitivity to paclitaxel and doxorubicin, suggesting a role for MALAT1 in conferring resistance. Mechanistically, whole transcriptome analysis of MALAT1-KO cells revealed multiple affected mechanistic networks as well as oxidative phosphorylation canonical and angiogenesis functional category. Interestingly, lncRNA profiling of MALAT1-depleted TNBC also revealed a number of altered lncRNAs in response to MALAT1 deletion, suggesting a reciprocal relationship between MALAT1 and a number of lncRNAs, including NEAT1, USP3-AS1, and LINC-PINT, in TNBC. Elevated expression of MALAT1, USP3-AS1, and LINC-PINT correlated with worse clinical outcomes in BC patients. Our data revealed the lncRNA transactional portrait and highlighted a complex regulatory network orchestrated by MALAT1 in the context of TNBC resistance to NAC therapy.
Computing conditional entropies for quantum correlations
Authors: Brown Peter , Fawzi Hamza , Fawzi Omar 
Published: January 2021

AbstractThe rates of quantum cryptographic protocols are usually expressed in terms of a conditional entropy minimized over a certain set of quantum states. In particular, in the device-independent setting, the minimization is over all the quantum states jointly held by the adversary and the parties that are consistent with the statistics that are seen by the parties. Here, we introduce a method to approximate such entropic quantities. Applied to the setting of device-independent randomness generation and quantum key distribution, we obtain improvements on protocol rates in various settings. In particular, we find new upper bounds on the minimal global detection efficiency required to perform device-independent quantum key distribution without additional preprocessing. Furthermore, we show that our construction can be readily combined with the entropy accumulation theorem in order to establish full finite-key security proofs for these protocols.
A co-design framework of neural networks and quantum circuits towards quantum advantage
Authors: Jiang Weiwen , Xiong Jinjun , Shi Yiyu 
Published: January 2021

AbstractDespite the pursuit of quantum advantages in various applications, the power of quantum computers in executing neural network has mostly remained unknown, primarily due to a missing tool that effectively designs a neural network suitable for quantum circuit. Here, we present a neural network and quantum circuit co-design framework, namely QuantumFlow, to address the issue. In QuantumFlow, we represent data as unitary matrices to exploit quantum power by encoding n = 2k inputs into k qubits and representing data as random variables to seamlessly connect layers without measurement. Coupled with a novel algorithm, the cost complexity of the unitary matrices-based neural computation can be reduced from O(n) in classical computing to O(polylog(n)) in quantum computing. Results show that on MNIST dataset, QuantumFlow can achieve an accuracy of 94.09% with a cost reduction of 10.85 × against the classical computer. All these results demonstrate the potential for QuantumFlow to achieve the quantum advantage.
Genetically encoded formaldehyde sensors inspired by a protein intra-helical crosslinking reaction
Authors: Zhu Rongfeng , Zhang Gong , Jing Miao , Han Yu , Li Jiaofeng , Zhao Jingyi , Li Yulong , Chen Peng R. 
Published: January 2021

AbstractFormaldehyde (FA) has long been considered as a toxin and carcinogen due to its damaging effects to biological macromolecules, but its beneficial roles have been increasingly appreciated lately. Real-time monitoring of this reactive molecule in living systems is highly desired in order to decipher its physiological and/or pathological functions, but a genetically encoded FA sensor is currently lacking. We herein adopt a structure-based study of the underlying mechanism of the FA-responsive transcription factor HxlR from Bacillus subtilis, which shows that HxlR recognizes FA through an intra-helical cysteine-lysine crosslinking reaction at its N-terminal helix α1, leading to conformational change and transcriptional activation. By leveraging this FA-induced intra-helical crosslinking and gain-of-function reorganization, we develop the genetically encoded, reaction-based FA sensor—FAsor, allowing spatial-temporal visualization of FA in mammalian cells and mouse brain tissues.
Conserved regulatory logic at accessible and inaccessible chromatin during the acute inflammatory response in mammals
Authors: Alizada Azad , Khyzha Nadiya , Wang Liangxi , Antounians Lina , Chen Xiaoting , Khor Melvin , Liang Minggao , Rathnakumar Kumaragurubaran , Weirauch Matthew T. , Medina-Rivera Alejandra , Fish Jason E. , Wilson Michael D. 
Published: January 2021

AbstractThe regulatory elements controlling gene expression during acute inflammation are not fully elucidated. Here we report the identification of a set of NF-κB-bound elements and common chromatin landscapes underlying the acute inflammatory response across cell-types and mammalian species. Using primary vascular endothelial cells (human/mouse/bovine) treated with the pro−inflammatory cytokine, Tumor Necrosis Factor-α, we identify extensive (~30%) conserved orthologous binding of NF-κB to accessible, as well as nucleosome-occluded chromatin. Regions with the highest NF-κB occupancy pre-stimulation show dramatic increases in NF-κB binding and chromatin accessibility post-stimulation. These ‘pre-bound’ regions are typically conserved (~56%), contain multiple NF-κB motifs, are utilized by diverse cell types, and overlap rare non-coding mutations and common genetic variation associated with both inflammatory and cardiovascular phenotypes. Genetic ablation of conserved, ‘pre-bound’ NF-κB regions within the super-enhancer associated with the chemokine-encoding CCL2 gene and elsewhere supports the functional relevance of these elements.
Caveolae-mediated Tie2 signaling contributes to CCM pathogenesis in a brain endothelial cell-specific Pdcd10-deficient mouse model
Authors: Zhou Huanjiao Jenny , Qin Lingfeng , Jiang Quan , Murray Katie N. , Zhang Haifeng , Li Busu , Lin Qun , Graham Morven , Liu Xinran , Grutzendler Jaime , Min Wang 
Published: January 2021

AbstractCerebral cavernous malformations (CCMs) are vascular abnormalities that primarily occur in adulthood and cause cerebral hemorrhage, stroke, and seizures. CCMs are thought to be initiated by endothelial cell (EC) loss of any one of the three Ccm genes: CCM1 (KRIT1), CCM2 (OSM), or CCM3 (PDCD10). Here we report that mice with a brain EC-specific deletion of Pdcd10 (Pdcd10BECKO) survive up to 6-12 months and develop bona fide CCM lesions in all regions of brain, allowing us to visualize the vascular dynamics of CCM lesions using transcranial two-photon microscopy. This approach reveals that CCMs initiate from protrusion at the level of capillary and post-capillary venules with gradual dissociation of pericytes. Microvascular beds in lesions are hyper-permeable, and these disorganized structures present endomucin-positive ECs and α-smooth muscle actin-positive pericytes. Caveolae in the endothelium of Pdcd10BECKO lesions are drastically increased, enhancing Tie2 signaling in Ccm3-deficient ECs. Moreover, genetic deletion of caveolin-1 or pharmacological blockade of Tie2 signaling effectively normalizes microvascular structure and barrier function with attenuated EC-pericyte disassociation and CCM lesion formation in Pdcd10BECKO mice. Our study establishes a chronic CCM model and uncovers a mechanism by which CCM3 mutation-induced caveolae-Tie2 signaling contributes to CCM pathogenesis.
Machine learning method for tight-binding Hamiltonian parameterization from ab-initio band structure
Authors: Wang Zifeng , Ye Shizhuo , Wang Hao , He Jin , Huang Qijun , Chang Sheng 
Published: January 2021

AbstractThe tight-binding (TB) method is an ideal candidate for determining electronic and transport properties for a large-scale system. It describes the system as real-space Hamiltonian matrices expressed on a manageable number of parameters, leading to substantially lower computational costs than the ab-initio methods. Since the whole system is defined by the parameterization scheme, the choice of the TB parameters decides the reliability of the TB calculations. The typical empirical TB method uses the TB parameters directly from the existing parameter sets, which hardly reproduces the desired electronic structures quantitatively without specific optimizations. It is thus not suitable for quantitative studies like the transport property calculations. The ab-initio TB method derives the TB parameters from the ab-initio results through the transformation of basis functions, which achieves much higher numerical accuracy. However, it assumes prior knowledge of the basis and may encompass truncation error. Here, a machine learning method for TB Hamiltonian parameterization is proposed, within which a neural network (NN) is introduced with its neurons acting as the TB matrix elements. This method can construct the empirical TB model that reproduces the given ab-initio energy bands with predefined accuracy, which provides a fast and convenient way for TB model construction and gives insights into machine learning applications in physical problems.
Recombinant MVA-prime elicits neutralizing antibody responses by inducing antigen-specific B cells in the germinal center
Authors: Eslamizar Leila , Petrovas Constantinos , Leggat David J. , Furr Kathryn , Lifton Michelle L. , Levine Gail , Ma Steven , Fletez-Brant Christopher , Hoyland Wesley , Prabhakaran Madhu , Narpala Sandeep , Boswell Kristin , Yamamoto Takuya , Liao Hua-Xin , Pickup David , Ramsburg Elizabeth , Sutherland Laura , McDermott Adrian , Roederer Mario , Montefiori David , Koup Richard A. , Haynes Barton F. , Letvin Norman L. , Santra Sampa 
Published: January 2021

AbstractThe RV144 HIV-1 vaccine trial has been the only clinical trial to date that has shown any degree of efficacy and associated with the presence of vaccine-elicited HIV-1 envelope-specific binding antibody and CD4+ T-cell responses. This trial also showed that a vector-prime protein boost combined vaccine strategy was better than when used alone. Here we have studied three different priming vectors—plasmid DNA, recombinant MVA, and recombinant VSV, all encoding clade C transmitted/founder Env 1086 C gp140, for priming three groups of six non-human primates each, followed by a protein boost with adjuvanted 1086 C gp120 protein. Our data showed that MVA-priming favors the development of higher antibody binding titers and neutralizing activity compared with other vectors. Analyses of the draining lymph nodes revealed that MVA-prime induced increased germinal center reactivity characterized by higher frequencies of germinal center (PNAhi) B cells, higher frequencies of antigen-specific B-cell responses as well as an increased frequency of the highly differentiated (ICOShiCD150lo) Tfh-cell subset.
A genome-wide investigation of the effect of farming and human-mediated introduction on the ubiquitous seaweed Undaria pinnatifida
Authors: Graf Louis , Shin Younhee , Yang Ji Hyun , Choi Ji Won , Hwang Il Ki , Nelson Wendy , Bhattacharya Debashish , Viard Frédérique , Yoon Hwan Su 
Published: January 2021

AbstractHuman activity is an important driver of ecological and evolutionary change on our planet. In particular, domestication and biological introductions have important and long-lasting effects on species’ genomic architecture and diversity. However, genome-wide analysis of independent domestication and introduction events within a single species has not previously been performed. The Pacific kelp Undaria pinnatifida provides such an opportunity because it has been cultivated in its native range in Northeast Asia but also introduced to four other continents in the past 50 years. Here we present the results of a genome-wide analysis of natural, cultivated and introduced populations of U. pinnatifida to elucidate human-driven evolutionary change. We demonstrate that these three categories of origin can be distinguished at the genome level, reflecting the combined influence of neutral (demography and migration) and non-neutral (selection) processes.
Hearing Aid Uptake, Benefit, and Use: The Impact of Hearing, Cognition, and Personal Factors
Authors: Nixon Grace , Sarant Julia , Tomlin Dani , Dowell Richard 
Published: January 2021

PurposeThe purpose of this study was to explore the effects of hearing, cognition, and personal factors on hearing aid (HA) uptake, use, and benefit.MethodEighty-five older adults aged 60–80 years (M= 70.23,SD= 5.17) participated in the study. Hearing was assessed using pure-tone audiometry and the Listening in Spatialised Noise–Sentences test. Cognition was measured using the Cogstate Brief Battery and the Cogstate Groton Maze Learning task. Personal demographics were recorded from participants' answers on a series of take-home questionnaires. HA benefit and use was subjectively reported at 3 and 6 months post HA fitting for those who chose to use HAs.ResultsStepwise-regression and mixed-effects models indicated that stronger psychomotor function predicted greater reported use of HAs at 3 and 6 months post HA fitting. Greater family interaction scores also predicted greater HA use at 3 months after fitting. Participants who chose to be fitted with HAs had significantly poorer self-reported health and poorer audiometric thresholds. Poorer hearing was also significantly related with greater reported HA benefit.ConclusionsA combination of cognitive, psychosocial factors and hearing impacted HA outcomes for the older Australians in this study. Self-reported HA use was significantly greater in participants with better psychomotor function. Furthermore, those with poorer self-reported health were more likely to choose to use HAs. These factors should be considered in audiological rehabilitation to best maximize patient HA outcomes.
City buses’ future velocity prediction for multiple driving cycle: A meta supervised learning solution
Authors: Cao Jianfei , He Hongwen , Cui Xing 
Published: January 2021

AbstractVehicular velocity prediction is of great significance to intelligent transportation system, as it provides a possible future velocity sequence for vehicle's decision‐making system. A velocity prediction method via meta learning is proposed, which provides an adaptive and generative framework for multiple‐driving cycles. The prediction model is devised using a deep neural network structure. The model's training is performed by the recently proposed meta‐supervised learning, which ensures that one trained model could meet the adaptability to multiple driving cycles. The complete framework consists of three parts: Pre‐training, fine‐tune‐training and real‐time prediction, which is tested to predict the hybrid electric city buses’ future velocity in a variable traffic scenario. The average prediction accuracy of 3, 5 and 10 s horizons is 0.51, 0.63 and 0.88 m s−1, which is 25.9%, 16.78% and 7.47% higher than that trained by the conventional supervised learning method. As suggested, the proposed prediction method is effective and could meet the requirement of energy‐saving control for hybrid electric city buses. With further study, potential application of this method may also exist in the field of driving behaviour prediction and transportation mode recognition.
Commissioning Measurements of Electron Beam Using Montecarlo Algorithm on Truebeam STx® and Compariaon with Clinac iX Linear Accelerator
Authors: Saidi Kamal , El Baydaoui Redouane , El Gouach Hanae , Kaanouch Othmane , Mesradi Mohamed Reda 
Published: January 2021

TrueBeam STx latest generation linear accelerators (linacs) installed at Sheikh Khalifa International University Hospital in Casablanca, Morocco.
The aim of this is to present and compare the result of the Electron commissioning measurement on TrueBeam Stx and clinac iX installed at Sheikh Khalifa International University Hospital in Casablanca, Morocco. A compariaon of eMC calculations and measurements for TrueBeam Stx were evaluated.
Dosimetric parameters are systematically measured using a large water phantom 3D scanning system MP3 Water Phantom (PTW, Freiburg, Germany). The data of the electron beams commissioning including depth dose curves for each applicator, depth dose curves without applicator and the profile in air for a large field size 40x 40cm2, and the Absolute Dose (cGy/MU) for each applicator. All the data were examined and compared for five electron beams (E6MeV, E9MeV, E12MeV, E16MeV and E20MeV) of Varian’s TrueBeam STx and Clinac iX machines.
A comparison, between measurement PDDs and calculated by the Eclipse electron Monte Carlo (eMC) algorithm were performed to validate Truebeam Stx commissioning. All this measurements were performed with a Roos and Markus plane parallel chamber.
Our measured data indicated that electron beam PDDs from the TrueBeam Stx machine are well matched to those from our Varian Clinac iX machine.
Significant differences between TrueBeam and Clinac iX were found in in‐air profiles and open field output. Maximum depth dose for the TrueBeam Stx and Clinac iX for the following energies (6, 9, 12, 16, 20 MeV) are respectively (1.15; 1.89; 2.6; 3.1; and 2.35) and (1.24; 1.95; 2.70; 2.99 and 2.4cm). For the TrueBeam Stx and Clinac iX the quality index R50 for applicator 15x15 cm2 are in the tolerance intervals. Surface dose increases by increasing energy for both machines.
The Absolute Dose (cGy/MU) calibrated for both machine in Dmax at 1cGy/MU for the reference field size cone 15x15 cm2.
Bremsstrahlung tail Rp per energy levels as follows for the TrueBeam Stx : 6 MeV – 2.85 cm, 9 MeV – 4.28 cm, 12 MeV – 5.97 cm, 16 MeV – 7.88 cm and 20 MeV – 9.86 cm. and for the
Clinac iX : 6 MeV – 2.86 cm, 9 MeV – 4.32 cm, 12 MeV – 5.96 cm, 16 MeV – 7.93 cm and 20 MeV – 10.08 cm.
A good agreement between modeled and measured data is observed.
Zusammenhang zwischen sozioökonomischem Status und Entwicklungsstand – Datenlinkage von Ergebnissen der Kita- und Schulaufnahmeuntersuchung mit einer sächsischen Geburtskohortenstudie
Authors: Redemann Dorothea , Arnold Katrin , Druschke Diana , Heinrich Luise , Rüdiger Mario , Reichert Jörg , Schmitt Jochen 
Published: January 2021

Zusammenfassung
Hintergrund Die kindliche Entwicklung ist durch biologische (z. B. Geschlecht, Geburtsreife) und psychosoziale Faktoren (z. B. sozioökonomischer Status, außerfamiliäre Tagesbetreuung) determiniert.
Ziel der Arbeit Es wurde die Stärke des Zusammenhanges zwischen dem familiären sozioökonomischen Status (SES) sowie biologischer und weiterer psychosozialer Faktoren und dem Entwicklungsstand von 4- und 6-jährigen Kindern untersucht.
Methodik Mittels Datenlinkage von Primärdaten einer Geburtskohortenstudie und Routinedaten der sächsischen Gesundheitsämter zu Kindern der Geburtsjahrgänge 2007 bis 2008, die sowohl die Kita- als auch die Schulaufnahmeuntersuchung durchlaufen hatten (N=615), wurden Auffälligkeiten der Sprache, Feinmotorik und Grobmotorik auf Zusammenhänge mit psychosozialen und biologischen Faktoren geprüft. Potenzielle Assoziationen wurden auf Signifikanz getestet sowie mittels binär logistischer Regression als Chancenverhältnis dargestellt.
Ergebnisse Der Großteil sächsischer Kinder entwickelte sich bis zum Schuleintritt unauffällig. Die Sprache zeigte sich jedoch mit Auffälligkeiten bei 37% der Kinder zu beiden Untersuchungszeitpunkten als sensibler Entwicklungsbereich. In beiden Altersgruppen waren Jungen, Frühgeborene und Kinder mit niedrigem SES häufiger von Entwicklungsverzögerungen betroffen. Frühgeborene mit niedrigem SES weisen das höchste Risikopotential auf. Weiterhin scheint dem außerfamiliären Betreuungsbeginn Bedeutung zuzukommen.
Schlussfolgerung Die Ergebnisse stehen in Einklang mit nationalen und internationalen Untersuchungsbefunden. Eine wichtige neue Erkenntnis ist die deutlich erhöhte Wahrscheinlichkeit für Entwicklungsauffälligkeiten beim Zusammentreffen biologischer und psychosozialer Risikofaktoren. Zur Betrachtung von Entwicklungsverläufen und zur Evaluation initiierter Maßnahmen sind jedoch Längsschnittanalysen erforderlich.
Stellenwert klinischer, funktioneller und bildgebender Diagnostik zur Früherkennung, Differenzialdiagnose und Verlaufskontrolle diabetischer Neuropathien
Authors: Dohrn Maike F. , Winter Natalie , Dumke Christina , Bähr Friederike , Ouwenbroek Annabelle , Hoppe Barbara , Reiners Karlheinz , Dafotakis Manuel 
Published: January 2021

ZusammenfassungVon weltweit mehr als 400 Mio. Menschen mit Diabetes mellitus entwickeln bis zu 50% im Laufe ihrer Erkrankung eine Neuropathie. Trotz oder gerade wegen dieser Häufigkeit darf jedoch nicht jede Neuropathie, die in Koinzidenz mit einem Diabetes mellitus auftritt, unkritisch als diabetische Neuropathie diagnostiziert werden. Eine präzise Ausschluss- und Ausmaßdiagnostik ist entscheidend, um andere behandelbare Erkrankungen wie z. B. die Chronisch Inflammatorische Demyelinisierende Polyradikuloneuropathie oder die hereditäre Transthyretin-Amyloidose nicht zu übersehen. Einfache, nicht-invasive, preiswerte und allzeit verfügbare Screeningmethoden stellen Anamnese und klinische Untersuchung dar. Ergänzend ist in frühen Erkrankungsstadien die Quantitativ Sensorische Testung hilfreich zur Eingrenzung einer Small Fiber-Dysfunktion. Sind, typischerweise im Verlauf, große Nervenfasern geschädigt, so ist das charakteristische elektrophysiologische Bild das einer längenabhängigen, axonalen, sensibel betonten oder sensomotorischen Neuropathie. Die Nervensonografie kann zur Unterscheidung von autoimmun-demyelinisierenden Neuropathien hilfreich sein. Moderne Untersuchungsverfahren wie die MR-Neurografie können auch proximale Nervenabschnitte bis auf Faszikelebene darstellen, sind allerdings nur an wenigen Zentren verfügbar. Haut- und Nervenbiopsien sind v. a. bei untypischen Verläufen zur Abgrenzung von Differenzialdiagnosen hilfreich. Diabetische Neuropathien können zu einer erheblichen Reduktion von Lebensqualität und Lebensdauer führen. Zur frühest- und bestmöglichen ursächlichen und symptomatischen Therapieeinleitung ist eine präzise Diagnostik essentiell.