bluuebunny/crossref_metadata_2025_split huggingface dataset:
The oncogenic fusion landscape in pediatric CNS neoplasms
Authors: Roosen Mieke , Odé Zelda , Bunt Jens , Kool Marcel 
Published: February 2022

AbstractPediatric neoplasms in the central nervous system (CNS) are the leading cause of cancer-related deaths in children. Recent developments in molecular analyses have greatly contributed to a more accurate diagnosis and risk stratification of CNS tumors. Additionally, sequencing studies have identified various, often entity specific, tumor-driving events. In contrast to adult tumors, which often harbor multiple mutated oncogenic drivers, the number of mutated genes in pediatric cancers is much lower and many tumors can have a single oncogenic driver. Moreover, in children, much more than in adults, fusion proteins play an important role in driving tumorigenesis, and many different fusions have been identified as potential driver events in pediatric CNS neoplasms. However, a comprehensive overview of all the different reported oncogenic fusion proteins in pediatric CNS neoplasms is still lacking. A better understanding of the fusion proteins detected in these tumors and of the molecular mechanisms how these proteins drive tumorigenesis, could improve diagnosis and further benefit translational research into targeted therapies necessary to treat these distinct entities. In this review, we discuss the different oncogenic fusions reported in pediatric CNS neoplasms and their structure to create an overview of the variety of oncogenic fusion proteins to date, the tumor entities they occur in and their proposed mode of action.
Mean-return-time phase of a stochastic oscillator provides an approximate renewal description for the associated point process
Authors: Holzhausen Konstantin , Ramlow Lukas , Pu Shusen , Thomas Peter J. , Lindner Benjamin 
Published: February 2022

AbstractStochastic oscillations can be characterized by a corresponding point process; this is a common practice in computational neuroscience, where oscillations of the membrane voltage under the influence of noise are often analyzed in terms of the interspike interval statistics, specifically the distribution and correlation of intervals between subsequent threshold-crossing times. More generally, crossing times and the corresponding interval sequences can be introduced for different kinds of stochastic oscillators that have been used to model variability of rhythmic activity in biological systems. In this paper we show that if we use the so-called mean-return-time (MRT) phase isochrons (introduced by Schwabedal and Pikovsky) to count the cycles of a stochastic oscillator with Markovian dynamics, the interphase interval sequence does not show any linear correlations, i.e., the corresponding sequence of passage times forms approximately a renewal point process. We first outline the general mathematical argument for this finding and illustrate it numerically for three models of increasing complexity: (i) the isotropic Guckenheimer–Schwabedal–Pikovsky oscillator that displays positive interspike interval (ISI) correlations if rotations are counted by passing the spoke of a wheel; (ii) the adaptive leaky integrate-and-fire model with white Gaussian noise that shows negative interspike interval correlations when spikes are counted in the usual way by the passage of a voltage threshold; (iii) a Hodgkin–Huxley model with channel noise (in the diffusion approximation represented by Gaussian noise) that exhibits weak but statistically significant interspike interval correlations, again for spikes counted when passing a voltage threshold. For all these models, linear correlations between intervals vanish when we count rotations by the passage of an MRT isochron. We finally discuss that the removal of interval correlations does not change the long-term variability and its effect on information transmission, especially in the neural context.
Geochemical Proxies and Mineralogical Fingerprints of Sedimentary Processes in a Closed Shallow Lake Basin Since 1850
Authors: Gravina Paola , Ludovisi Alessandro , Moroni Beatrice , Vivani Riccardo , Selvaggi Roberta , Petroselli Chiara , Cappelletti David 
Published: February 2022

AbstractLake systems are essential for the environment, the biosphere, and humans but are highly impacted by anthropogenic activities accentuated by climate change. Understanding how lake ecosystems change due to human impacts and natural forces is crucial to managing their current state and possible future restoration. The high sensitivity of shallow closed lakes to natural and anthropogenic forcing makes these lacustrine ecosystems highly prone to variations in precipitation and sedimentation processes. These variation processes, occurring in the water column, produce geochemical markers or proxies recorded in lake sedimentary archives. This study investigated specific proxies on high-resolution sedimentary archives (2–3 years resolution) of the Trasimeno lake (Central Italy). The Trasimeno lake underwent three different hydrological phases during the twentieth century due to several fluctuations induced mainly by human activities and climate change. The Trasimeno lake, a large and shallow basin located in the Mediterranean area, is a good case study to assess the effects of intense anthropogenic activity related to agriculture, tourism, industry, and climate changes during the Anthropocene. The aim is to identify the main characteristics of the main sedimentary events in the lake during the last 150 years, determining the concentrations of major and trace elements, the amount of organic matter, and the mineralogical composition of the sediments. This type of work demonstrates that studying sediment archives at high resolution is a viable method for reconstructing the lake’s history through the evolution/trends of the geochemical proxies stored in the sediment records. This effort makes it possible to assess past anthropogenic impact and, under the objectives of the European Green Deal (zero-pollution ambition for a toxic-free environment), to monitor, prevent, and remedy pollution related to soil and water compartments.
Graphical abstract
Newtonian Equivalence Principles
Authors: Read James , Teh Nicholas J. 
Published: February 2022

AbstractThe equivalence principle has constituted one of the cornerstones of discussions in the foundations of spacetime theories over the past century. However, up to this point the principle has been considered overwhelmingly only within the context of relativistic physics. In this article, we demonstrate that the principle has much broader, super-theoretic significance: to do so, we present a unified framework for understanding the principle in its various guises, applicable to both relativistic and Newtonian contexts. We thereby deepen significantly our understanding of the role played by the equivalence principle in a broad class of spacetime theories.
Effects of Similarity Score Functions in Attention Mechanisms on the Performance of Neural Question Answering Systems
Authors: Shen Yuanyuan , Lai Edmund M.-K. , Mohaghegh Mahsa 
Published: February 2022

AbstractAttention mechanisms have been incorporated into many neural network-based natural language processing (NLP) models. They enhance the ability of these models to learn and reason with long input texts. A critical part of such mechanisms is the computation of attention similarity scores between two elements of the texts using a similarity score function. Given that these models have different architectures, it is difficult to comparatively evaluate the effectiveness of different similarity score functions. In this paper, we proposed a baseline model that captures the common components of recurrent neural network-based Question Answering (QA) systems found in the literature. By isolating the attention function, this baseline model allows us to study the effects of different similarity score functions on the performance of such systems. Experimental results show that a trilinear function produced the best results among the commonly used functions. Based on these insights, a new T-trilinear similarity function is proposed which achieved the higher predictive EM and F1 scores than these existing functions. A heatmap visualization of the attention score matrix explains why this T-trilinear function is effective.
A Systematic Review of the Reporting Quality of Observational Studies That Use Mediation Analyses
Authors: Rizzo Rodrigo R. N. , Cashin Aidan G. , Bagg Matthew K. , Gustin Sylvia M. , Lee Hopin , McAuley James H. 
Published: February 2022

AbstractMediation analysis is a common statistical method used to investigate mechanisms of health exposure and interventions. The reporting quality of mediation studies used in randomised controlled trials has been considered heterogeneous and incomplete. The reporting quality of mediation analysis in observational studies is unknown. We conducted a systematic review to describe the reporting standards of recently published observational studies that used mediation analysis to understand the mechanism of health exposures. We searched for studies published between June 2017 and June 2019 indexed in EMBASE, MEDLINE and PsycINFO. Two reviewers screened articles and selected a random sample of 50 eligible studies for inclusion. We included studies across 13 healthcare fields and ten different health conditions. Most studies (74%) collected data on healthy individuals to assess their risk of developing a health disorder. Psychosocial and behavioural factors (self-control, self-esteem, alcohol consumption, pain) were the most prevalent exposures (n = 30, 60%), outcomes (n = 23, 46%) and mediators (n = 29, 58%). Most studies used a cross-sectional design (64%, n = 32), and a few studies reported sample size calculations (4%, n = 8). In 20% (n = 10) of the studies, adjustment for confounders was reported. Only 10% (n = 5) of studies reported the assumptions underlying the mediation analysis, and 14% (n = 7) of studies conducted some sensitivity analysis to assess the degree which unmeasured confounders would affect the estimate of the mediation effect. Mediation analysis is a common method used to investigate mechanisms in prevention research. The reporting of mediation analysis in observational studies is incomplete and may impact reproducibility, evidence synthesis and implementation.
Augmented pseudo-marginal Metropolis–Hastings for partially observed diffusion processes
Authors: Golightly Andrew , Sherlock Chris 
Published: February 2022

AbstractWe consider the problem of inference for nonlinear, multivariate diffusion processes, satisfying Itô stochastic differential equations (SDEs), using data at discrete times that may be incomplete and subject to measurement error. Our starting point is a state-of-the-art correlated pseudo-marginal Metropolis–Hastings algorithm, that uses correlated particle filters to induce strong and positive correlation between successive likelihood estimates. However, unless the measurement error or the dimension of the SDE is small, correlation can be eroded by the resampling steps in the particle filter. We therefore propose a novel augmentation scheme, that allows for conditioning on values of the latent process at the observation times, completely avoiding the need for resampling steps. We integrate over the uncertainty at the observation times with an additional Gibbs step. Connections between the resulting pseudo-marginal scheme and existing inference schemes for diffusion processes are made, giving a unified inference framework that encompasses Gibbs sampling and pseudo marginal schemes. The methodology is applied in three examples of increasing complexity. We find that our approach offers substantial increases in overall efficiency, compared to competing methods
Review of imaging techniques for evaluating morphological and functional responses to the treatment of bone metastases in prostate and breast cancer
Authors: Orcajo-Rincon J. , Muñoz-Langa J. , Sepúlveda-Sánchez J. M. , Fernández-Pérez G. C. , Martínez M. , Noriega-Álvarez E. , Sanz-Viedma S. , Vilanova J. C. , Luna A. 
Published: February 2022

AbstractBone metastases are very common complications associated with certain types of cancers that frequently negatively impact the quality of life and functional status of patients; thus, early detection is necessary for the implementation of immediate therapeutic measures to reduce the risk of skeletal complications and improve survival and quality of life. There is no consensus or universal standard approach for the detection of bone metastases in cancer patients based on imaging. Endorsed by the Spanish Society of Medical Oncology (SEOM), the Spanish Society of Medical Radiology (SERAM), and the Spanish Society of Nuclear Medicine and Molecular Imaging (SEMNIM) a group of experts met to discuss and provide an up-to-date review of our current understanding of the biological mechanisms through which tumors spread to the bone and describe the imaging methods available to diagnose bone metastasis and monitor their response to oncological treatment, focusing on patients with breast and prostate cancer. According to current available data, the use of next-generation imaging techniques, including whole-body diffusion-weighted MRI, PET/CT, and PET/MRI with novel radiopharmaceuticals, is recommended instead of the classical combination of CT and bone scan in detection, staging and response assessment of bone metastases from prostate and breast cancer.Clinical trial registration: Not applicable.
Improving Antibacterial Efficiency of Curcumin in Magnetic Polymeric Nanocomposites
Authors: Sadeghi-Ghadi Zaynab , Behjou Nicki , Ebrahimnejad Pedram , Mahkam Mehrdad , Goli Hamid Reza , Lam Matthew , Nokhodchi Ali 
Published: February 2022

AbstractIn recent years, resistance to chemical antibiotics, as well as their side effects, has caused a necessity to utilize natural substances and herbal components with antibacterial effects. Curcumin, the major substance of Curcuma longa’s rhizome, was used as an antibacterial agent since ancient times. This work aimed to formulate a novel nanocomposite for the delivery of curcumin to overcome orthodox drugs resistance against bacteria and improve its efficacy. To fabricate targeting nanocomposites, first, Fe3O4 nanoparticles were synthesized followed by coating the obtained nanoparticles using sodium alginate containing curcumin. A 2 by 3 factorial design was tailored to predict the optimum formulation of nanocomposites. Characterization of nanocomposites including particle size, polydispersity index (PDI), zeta potential, entrapment efficiency, and drug loading was performed. The optimum formulation was analyzed by differential scanning calorimetry (DSC), scanning electron microscopy (SEM), Fourier-transformed infrared spectroscopy (FT-IR), and in vitro release study at different pHs. Finally, minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) of samples against seven common bacteria were determined. Results showed that the optimized formulation contained 400 nm particles with the PDI and zeta potentials of 0.4 and − 58 mV, respectively. The optimized formulation with 70% entrapment efficiency reduced the MIC value 2 to 4 times in comparison with pure curcumin. Results also showed that polymer and drug concentrations can significantly affect entrapment efficiency. In conclusion, the current investigation demonstrated that this magnetic nanocomposite can be applied for the delivery of curcumin.
Graphical abstract
Maßgeschneiderte Hefezellen für biotechnologische Anwendungen
Authors: Oreb Mislav , Tripp Joanna 
Published: February 2022

AbstractThe tremendous body of knowledge about genetics, cell biology, and metabolism of Saccharomyces cerevisiae, as well as its long history and robustness in industrial fermentations, have made this yeast one of the most popular microbial cell factories. Novel genetic tools have enabled the rapid construction of strains producing various platform chemicals, fuels, or pharmaceuticals. The relevance of synthetic biology approaches, such as the construction of fully synthetic genomes and artificial cellular compartments are not only relevant for biotechnological applications but can also lead to new insight into basic principles of life.
Mitochondrien: wie die Gene im Kraftwerk der Zelle aktiviert werden
Authors: Bhatta Arjun , Hillen Hauke S. 
Published: February 2022

AbstractMitochondria contain an organellar genome that encodes for subunits of the respiratory chain. Its coordinated expression is essential for eukaryotic life and defects in this process lead to severe disease. However, the molecular mechanisms underlying mitochondrial gene expression remain poorly understood. Recent structural and functional studies have provided the first mechanistic insights into mitochondrial gene expression and highlight the evolutionarily unique nature of this system.
On -approachability, entropy density and -free shifts
Authors: KONIECZNY JAKUB , KUPSA MICHAL , KWIETNIAK DOMINIK 
Published: February 2022

AbstractWe study approximation schemes for shift spaces over a finite alphabet using (pseudo)metrics connected to Ornstein’s
${\bar d}$
metric. This leads to a class of shift spaces we call
${\bar d}$
-approachable. A shift space is
${\bar d}$
-approachable when its canonical sequence of Markov approximations converges to it also in the
${\bar d}$
sense. We give a topological characterization of chain-mixing
${\bar d}$
-approachable shift spaces. As an application we provide a new criterion for entropy density of ergodic measures. Entropy density of a shift space means that every invariant measure
$\mu $
of such a shift space is the weak
$^*$
limit of a sequence
$\mu _n$
of ergodic measures with the corresponding sequence of entropies
$h(\mu _n)$
converging to
$h(\mu )$
. We prove ergodic measures are entropy-dense for every shift space that can be approximated in the
${\bar d}$
pseudometric by a sequence of transitive sofic shifts. This criterion can be applied to many examples that were beyond the reach of previously known techniques including hereditary
$\mathscr {B}$
-free shifts and some minimal or proximal systems. The class of symbolic dynamical systems covered by our results includes also shift spaces where entropy density was established previously using the (almost) specification property.
THE p-ADIC GROSS–ZAGIER FORMULA ON SHIMURA CURVES, II: NONSPLIT PRIMES
Authors: Disegni Daniel 
Published: February 2022

AbstractThe formula of the title relates p-adic heights of Heegner points and derivatives of p-adic L-functions. It was originally proved by Perrin-Riou for p-ordinary elliptic curves over the rationals, under the assumption that p splits in the relevant quadratic extension. We remove this assumption, in the more general setting of Hilbert-modular abelian varieties.
Multivariate Bias‐Correction of High‐Resolution Regional Climate Change Simulations for West Africa: Performance and Climate Change Implications
Authors: Dieng Diarra , Cannon Alex J. , Laux Patrick , Hald Cornelius , Adeyeri Oluwafemi , Rahimi Jaber , Srivastava Amit K. , Mbaye Mamadou Lamine , Kunstmann Harald 
Published: February 2022

AbstractA multivariate bias correction based on N‐dimensional probability density function transform (MBCn) technique is applied to four different high‐resolution regional climate change simulations and key meteorological variables, namely precipitation, mean near‐surface air temperature, near‐surface maximum air temperature, near‐surface minimum air temperature, surface downwelling solar radiation, relative humidity, and wind speed. The impact of bias‐correction on the historical (1980–2005) period, the inter‐variable relationships, and the measures of spatio‐temporal consistency are investigated. The focus is on the discrepancies between the original and the bias‐corrected results over five agro‐ecological zones. We also evaluate relevant indices for agricultural applications such as climate extreme indices, under current and future (2020–2050) climate change conditions based on the RCP4.5. Results show that MBCn successfully corrects the seasonal biases in spatial patterns and intensities for all variables, their intervariable correlation, and the distributions of most of the analyzed variables. Relatively large bias reductions during the historical period give indication of possible benefits of MBCn when applied to future scenarios. Although the four regional climate models do not agree on the same positive/negative sign of the change of the seven climate variables for all grid points, the model ensemble mean shows a statistically significant change in rainfall, relative humidity in the Northern zone and wind speed in the Coastal zone of West Africa and increasing maximum summer temperature up to 2°C in the Sahara.
Lunar Wrinkle Ridges and the Evolution of the Nearside Lithosphere
Authors: Watters Thomas R. 
Published: February 2022

AbstractWrinkle ridges are the largest and most morphologically complex contractional landforms found on the Moon. They occur exclusively in mare basalt and are thought to result from load induced subsidence and flexure of the lunar lithosphere. The displacement‐length (Dmax/L) relations of wrinkle ridge thrust faults in mascons, where mare basalts are generally thickest, and non‐mascon settings are compared. The results show no statistically significant difference in the population γ values of the wrinkle ridges. Dmax/L values of ridge faults are distributed over the entire range of the sampled population regardless of setting. This suggests that the elastic lithosphere supporting the nearside mare accommodated comparable ridge formation in non‐mascons, with generally thinner sequences of load inducing mare basalt, to mascons. Analysis of the heat flow suggests the elastic lithosphere supporting non‐mascons may have been relatively thin when wrinkle ridge formation began, possibly accounting for the similarity in Dmax/L values with ridges in mascons. Thickening of the elastic lithosphere over time is expected to result in a progression in age of wrinkle ridges in mascon and non‐mascon from oldest near mare centers to younger at the margins.