bluuebunny/crossref_metadata_2025_split huggingface dataset:
Modeling rod and cone photoreceptor cell survival in vivo using optical coherence tomography
Authors: Whitmore S. Scott , DeLuca Adam P. , Andorf Jeaneen L. , Cheng Justine L. , Mansoor Mahsaw , Fortenbach Christopher R. , Critser D. Brice , Russell Jonathan F. , Stone Edwin M. , Han Ian C. 
Published: April 2023

AbstractMany retinal diseases involve the loss of light-sensing photoreceptor cells (rods and cones) over time. The severity and distribution of photoreceptor loss varies widely across diseases and affected individuals, so characterizing the degree and pattern of photoreceptor loss can clarify pathophysiology and prognosis. Currently, in vivo visualization of individual photoreceptors requires technology such as adaptive optics, which has numerous limitations and is not widely used. By contrast, optical coherence tomography (OCT) is nearly ubiquitous in daily clinical practice given its ease of image acquisition and detailed visualization of retinal structure. However, OCT cannot resolve individual photoreceptors, and no OCT-based method exists to distinguish between the loss of rods versus cones. Here, we present a computational model that quantitatively estimates rod versus cone photoreceptor loss from OCT. Using histologic data of human photoreceptor topography, we constructed an OCT-based reference model to simulate outer nuclear layer thinning caused by differential loss of rods and cones. The model was able to estimate rod and cone loss using in vivo OCT data from patients with Stargardt disease and healthy controls. Our model provides a powerful new tool to quantify photoreceptor loss using OCT data alone, with potentially broad applications for research and clinical care.
Prepandemic psychotropic drug status in Portugal: a nationwide pharmacoepidemiological profile﻿
Authors: Madeira Luís , Queiroz Guilherme , Henriques Rui 
Published: April 2023

AbstractThe prescription of psychotropic drugs has been rising in Europe over the last decade. This study provides a comprehensive profile of prepandemic consumption patterns of antidepressant, antipsychotic, and anxiolytic drugs in Portugal considering full nationwide psychotropic drug prescription and dispensing records (2016–2019) against several criteria, including active ingredient, sociodemographics, medical specialty, and incurred costs. An increase of 29.6% and 34.7% in the consumption of antipsychotics and antidepressants between 2016 and 2019 is highlighted, accompanied by an increase of 37M Eur in total expenditure (> 20M Eur in public copay) for these classes of drugs. Disparities in sociodemographic and geographical incidence are identified. Amongst other pivotal results, 64% of psychotropic drug prescriptions are undertaken by general practitioners, while only 21% undertaken by neurological and psychiatric specialties. Nationwide patterns of psychotropic drug prescription further reveal notable trends and determinants, establishing a reference point for cross-regional studies and being currently assessed at a national level to establish psychosocial initiatives and guidelines for medical practice and training.
Computer-aided detection of arrhythmogenic sites in post-ischemic ventricular tachycardia
Authors: Baldazzi Giulia , Orrù Marco , Viola Graziana , Pani Danilo 
Published: April 2023

AbstractNowadays, catheter-based ablation in patients with post-ischemic ventricular tachycardia (VT) is performed in arrhythmogenic sites identified by electrophysiologists by visual inspection during electroanatomic mapping. This work aims to present the development of machine learning tools aiming at supporting clinicians in the identification of arrhythmogenic sites by exploiting innovative features that belong to different domains. This study included 1584 bipolar electrograms from nine patients affected by post-ischemic VT. Different features were extracted in the time, time scale, frequency, and spatial domains and used to train different supervised classifiers. Classification results showed high performance, revealing robustness across the different classifiers in terms of accuracy, true positive, and false positive rates. The combination of multi-domain features with the ensemble tree is the most effective solution, exhibiting accuracies above 93% in the 10-time 10-fold cross-validation and 84% in the leave-one-subject-out validation. Results confirmed the effectiveness of the proposed features and their potential use in a computer-aided system for the detection of arrhythmogenic sites. This work demonstrates for the first time the usefulness of supervised machine learning for the detection of arrhythmogenic sites in post-ischemic VT patients, thus enabling the development of computer-aided systems to reduce operator dependence and errors, thereby possibly improving clinical outcomes.
A novel hybrid protein composed of superoxide-dismutase-active Cu(II) complex and lysozyme
Authors: Furuya Tetsundo , Nakane Daisuke , Kitanishi Kenichi , Katsuumi Natsuki , Tsaturyan Arshak , Shcherbakov Igor N. , Unno Masaki , Akitsu Takashiro 
Published: April 2023

AbstractA novel hybrid protein composed of a superoxide dismutase-active Cu(II) complex (CuST) and lysozyme (CuST@lysozyme) was prepared. The results of the spectroscopic and electrochemical analyses confirmed that CuST binds to lysozyme. We determined the crystal structure of CuST@lysozyme at 0.92 Å resolution, which revealed that the His15 imidazole group of lysozyme binds to the Cu(II) center of CuST in the equatorial position. In addition, CuST was fixed in position by the weak axial coordination of the Thr89 hydroxyl group and the hydrogen bond between the guanidinium group of the Arg14 residue and the hydroxyl group of CuST. Furthermore, the combination of CuST with lysozyme did not decrease the superoxide dismutase activity of CuST. Based on the spectral, electrochemical, structural studies, and quantum chemical calculations, an O2– disproportionation mechanism catalyzed by CuST@lysozyme is proposed.
Low rates of bacterivory enhances phototrophy and competitive advantage for mixoplankton growing in oligotrophic waters
Authors: Mitra Aditee , Flynn Kevin J. 
Published: April 2023

AbstractWith climate change, oceans are becoming increasingly nutrient limited, favouring growth of prokaryotic picoplankton at the expense of the larger protist plankton whose growth support higher trophic levels. Constitutive mixoplankton (CM), microalgal plankton with innate phototrophic capability coupled with phagotrophy, graze on these picoplankton, indirectly exploiting the excellent resource acquisition abilities of the prokaryotes. However, feeding rates can be very low (e.g., a few bacteria d−1). For the first time, the significance of such low consumption rates has been quantified. We find that while prokaryote-carbon (C) supply to CM grown at non-limiting light was so low that it may appear insignificant (< 10%), contributions of nitrogen (N) and phosphorus (P) from ingestions of 1–12 prokaryotes d−1 were significant. Under limiting light, contributions of ingested C increased, also raising the contributions of N and P. The order of nutritional importance for CM growth from predation was P > N > C. Further, provision of N through internal recycling of ingested prey-N stimulates C-fixation through photosynthesis. Importantly, coupled photo-phago-mixoplanktonic activity improved CM resource affinities for both inorganic and prey-bound nutrients, enhancing the nutritional status and competitiveness of mixoplankton. With warming oceans, with increased prokaryote abundance, we expect CM to exhibit more phagotrophy.
A link prediction-based recommendation system using transactional data
Authors: Yilmaz Emir Alaattin , Balcisoy Selim , Bozkaya Burcin 
Published: April 2023

AbstractRecommending relevant items to users has become an important task in many systems due to the increased amount of data produced. For this purpose, transaction datasets such as credit card transactions and e-commerce purchase histories can be used in recommendation systems to understand underlying user interests by exploiting user-item interactions, which can be a powerful signal to perform this task. This study proposes a link prediction-based recommendation system combining graph representation learning algorithms and gradient boosting classifiers for transaction datasets. The proposed system generates a network where nodes correspond to users and items, and links represent their interactions. A use case scenario is examined on a credit card transaction dataset as a merchant prediction task that predicts the merchants where users can make purchases in the next month. Performances of common network embedding extraction techniques and classifier models are evaluated via various experiments conducted and based on these evaluations, a novel system is proposed, and a matrix factorization-based alternative recommendation method is compared with the proposed model. The proposed method has shown superior performance to the alternative method in terms of receiver operating characteristic curves, area under the curve, and mean average precision metrics. The use of transactional data for a recommendation system is found to be a powerful approach to making relevant recommendations.
Root and canal morphology of third molar teeth
Authors: Al-Qudah Aladdin Ahmad , Bani Younis Hamzeh A. Barakat , Awawdeh Lama Adel , Daud Alaa 
Published: April 2023

AbstractRestorative and prosthetic considerations usually necessitates endodontic treatment of third molars in order to retain them as a functional component of the dental arch. However, the anatomy of third molars has been described as unpredictable. To date, there has been little published work on root and canal morphology of third molars, with an adequate sample size. The aim of this study was to investigate root and canal morphology of third molars. Maxillary and mandibular third molars were gathered from dental surgeries within north Jordan. Following access cavity preparation, pulp tissue was removed and root canals stained. Teeth were subject to examination after rendering them clear by immersion in methyl salicylate, and the following features evaluated: (1) number of roots; (2) number and type of root canals; (3) number and position of lateral canals; and (4) presence of inter-canal communications. Out of the examined 592 maxillary third molars, 69.9% had three roots, 10.81% had one, 9.79% had two, 9.12% had four, and 0.34% had five roots. Most had three (52.36%) and four canals (28.2%) with less frequency of two (11.48%), one (5.91%) and five canals (2.03%). Of the 639 mandibular third molars, 89.76% had two roots, 7.35% had three, 2.5% had one, and 0.47% had four roots. Most had three (55.71%) and two canals (29.42%) with less frequency of four (13.61%), one (1.09%) and five canals (0.15%). The majority of maxillary third molars had 3 roots, while the majority of mandibular third molars had two. Overall, nearly half of the maxillary and mandibular third molars had three canals. New canal configurations, not previously described in the literature nor included in Vertucci’s classifications, were identified in both maxillary and mandibular third molars.
High Chern number van der Waals magnetic topological multilayers MnBi2Te4/hBN
Authors: Bosnar Mihovil , Vyazovskaya Alexandra Yu. , Petrov Evgeniy K. , Chulkov Evgueni V. , Otrokov Mikhail M. 
Published: April 2023

AbstractChern insulators are two-dimensional magnetic topological materials that conduct electricity along their edges via the one-dimensional chiral modes. The number of these modes is a topological invariant called the first Chern numberCthat defines the quantized Hall conductance asSxy = Ce2/h. IncreasingCis pivotal for the realization of low-power-consumption topological electronics, but there has been no clear-cut solution to this problem so far, with the majority of existing Chern insulators showingC = 1. Here, by using state-of-the-art theoretical methods, we propose an efficient approach for the realization of the high-Cstate in MnBi2Te4/hBN van der Waals multilayer heterostructures. We show that a stack ofnMnBi2Te4films withC = 1 intercalated by hBN monolayers gives rise to a high Chern number state withC = n, characterized bynchiral edge modes. This state can be achieved both under the external magnetic field and without it, both cases leading to the quantized Hall conductanceSxy = Ce2/h. Our results, therefore, pave the way to practical high-Cquantized Hall systems.
Automated relative binding free energy calculations from SMILES to ΔΔG
Authors: Moore J. Harry , Margreitter Christian , Janet Jon Paul , Engkvist Ola , de Groot Bert L. , Gapsys Vytautas 
Published: April 2023

AbstractIn drug discovery, computational methods are a key part of making informed design decisions and prioritising experiments. In particular, optimizing compound affinity is a central concern during the early stages of development. In the last 10 years, alchemical free energy (FE) calculations have transformed our ability to incorporate accurate in silico potency predictions in design decisions, and represent the ‘gold standard’ for augmenting experiment-driven drug discovery. However, relative FE calculations are complex to set up, require significant expert intervention to prepare the calculation and analyse the results or are provided only as closed-source software, not allowing for fine-grained control over the underlying settings. In this work, we introduce an end-to-end relative FE workflow based on the non-equilibrium switching approach that facilitates calculation of binding free energies starting from SMILES strings. The workflow is implemented using fully modular steps, allowing various components to be exchanged depending on licence availability. We further investigate the dependence of the calculated free energy accuracy on the initial ligand pose generated by various docking algorithms. We show that both commercial and open-source docking engines can be used to generate poses that lead to good correlation of free energies with experimental reference data.
Mass spectrometric simultaneous quantification of tau species in plasma shows differential associations with amyloid and tau pathologies
Authors: Montoliu-Gaya Laia , Benedet Andréa L. , Tissot Cécile , Vrillon Agathe , Ashton Nicholas J. , Brum Wagner S. , Lantero-Rodriguez Juan , Stevenson Jenna , Nilsson Johanna , Sauer Mathias , Rahmouni Nesrine , Brinkmalm Gunnar , Lussier Firoza Z. , Pascoal Tharick A. , Skoog Ingmar , Kern Silke , Zetterberg Henrik , Paquet Claire , Gobom Johan , Rosa-Neto Pedro , Blennow Kaj 
Published: April 2023

AbstractBlood phosphorylated tau (p-tau) biomarkers, at differing sites, demonstrate high accuracy to detect Alzheimerʼs disease (AD). However, knowledge on the optimal marker for disease identification across the AD continuum and the link to pathology is limited. This is partly due to heterogeneity in analytical methods. In this study, we employed an immunoprecipitation mass spectrometry method to simultaneously quantify six phosphorylated (p-tau181, p-tau199, p-tau202, p-tau205, p-tau217 and p-tau231) and two non-phosphorylated plasma tau peptides in a total of 214 participants from the Paris Lariboisière and Translational Biomarkers of Aging and Dementia cohorts. Our results indicate that p-tau217, p-tau231 and p-tau205 are the plasma tau forms that best reflect AD-related brain changes, although with distinct emergences along the disease course and correlations with AD features—amyloid and tau. These findings support the differential association of blood p-tau variants with AD pathology, and our method offers a potential tool for disease staging in clinical trials.
Quantifying the capacity credit of IDC‐based demand response in smart distribution systems
Authors: Zeng Bo , Zhang Changhao , Hu Pinduan , Yang Fulin , Li Weikang , Mu Hongwei 
Published: May 2023

AbstractWith the explosive growth of online services, the Internet Data Center (IDC) has become an emerging load demand . The power consumption of IDCs are believed suitable for demand response (DR) purposes due to its temporal‐spatial flexibility properties. To what extent IDCs could be used as candidate DR resources to provide capacity support are dependent both on the technical property and the willingness of data end‐users . To address the above issue, this paper presents a methodological framework for quantifying the potential value of IDC‐based DR in distribution grids. To achieve this, the concept of capacity credit (CC) is introduced and extended into the IDC scenario. The proposed framework explicitly considered the impacts of uncertainty of user participation intention and the reliability of basic information in the DR process. A novel Z‐number based price elasticity uncertainty model is introduced, and a more realistic evaluation of IDC capacity credit is obtained. Finally, the effectiveness of the proposed model and method is illustrated on a modified IEEE‐33 node network, and the obtained results verify the significance of IDC‐based DR in enhancing the adequacy of supply in distribution grids.
Dynamic interactive characteristics between icicle growth and corona discharge on HVDC outdoor insulators during icing accretion
Authors: Liu Yong , Li Chao , Yin Fanghui , Du Boxue , Farzaneh Masoud 
Published: April 2023

AbstractIn order to improve the stability and reliability of high voltage direct current (HVDC) transmission lines in cold regions, this article investigated the corona discharges and the icicle growth characteristics on outdoor insulators under DC voltages. The experiments were conducted at CIGELE laboratory at University of Quebec. The simulation model of corona discharges and the theoretical model of icicle growth were established. The dynamic process and interactive characteristics between the icicle growth and corona discharges under different HVDC voltages were obtained. The results showed that the discharge activity was strong and the cooling effect of ionic air was weak under negative DC voltage, resulting in a large number of bubbles inside the icicle. More negative ions were produced under negative DC voltage, which enhanced the polarisation of water droplets, leading to a greater density of ice beads outside the icicles. In addition, the longest icicles of each insulator under high humidity could bridge the shed gap. The accumulated charge and leakage current were higher under negative DC voltage, as well as the corona discharge at the top of the icicles lasted longer. Therefore, the negative DC corona discharge more significantly inhibited the growth of the icicle, resulting in a slower growth rate of the icicles.
Robust joint transmit and receive beamforming by sequential optimization for bistatic radar system
Authors: Li Haoran , Geng Jun , Xie Junhao 
Published: April 2023

AbstractThe conventional joint transmit and receive beamforming algorithms maximise the output signal‐to‐interference‐plus‐noise ratio (SINR) by designing the weight coefficients simultaneously at the transmitter and receiver. However, their performance degrades significantly when the model mismatch exists. In this paper, the robust version of the joint transmit and receive beamforming method is considered in the context of the bistatic radar system. In particular, both the transmit array and the receive array suffer model mismatch. The designed beamformer aims to maximise its output SINR subjected to a robustness constraint by simultaneously designing the transmit beamforming vector and the receive beamforming vector. Two types of robustness constraints, namely the worst‐case constraint and the probability constraint, are considered in this paper. The proposed formulations are non‐convex, and the sub‐optimal solutions are obtained by a sequential optimization approach. In addition, a novel method to estimate the interference‐plus‐noise covariance matrices at the transmitter and receiver is proposed, which makes the proposed robust joint beamforming algorithms adapt to the variation of the surrounding environment. Numerical simulations verify the effectiveness of the proposed algorithms.
The interplay between pebble and planetesimal accretion in population synthesis models and its role in giant planet formation
Authors: Kessler A. , Alibert Y. 
Published: April 2023

Context. In the core accretion scenario of planet formation, rocky cores grow by first accreting solids until they are massive enough to accrete gas. For giant planet formation, this means that a massive core must form within the lifetime of the gas disk. Inspired by observations of Solar System features such as the asteroid and Kuiper belts, the accretion of roughly kilometre-sized planetesimals is traditionally considered as the main accretion mechanism of solids but such models often result in longer planet formation timescales. The accretion of millimetre- to centimetre-sized pebbles, on the other hand, allows for rapid core growth within the disk lifetime. The two accretion mechanisms are typically discussed separately.
Aims. We investigate the interplay between the two accretion processes in a disk containing both pebbles and planetesimals for planet formation in general and in the context of giant planet formation specifically. The goal is to disentangle and understand the fundamental interactions that arise in such hybrid pebble-planetesimal models laying the groundwork for informed analysis of future, more complex, simulations.
Methods. We combined a simple model of pebble formation and accretion with a global model of planet formation which considers the accretion of planetesimals. We compared synthetic populations of planets formed in disks composed of different amounts of pebbles and 600 metre-sized planetesimals to identify the impact of the combined accretion scenario. On a system level, we studied the formation pathway of giant planets in these disks.
Results. We find that, in hybrid disks containing both pebbles and planetesimals, the formation of giant planets is strongly suppressed, whereas, in a pebbles-only or planetesimals-only scenario, giant planets can form. We identify the heating associated with the accretion of up to 100 kilometre-sized planetesimals after the pebble accretion period to delay the runaway gas accretion of massive cores. Coupled with strong inward type-I migration acting on these planets, this results in close-in icy sub-Neptunes originating from the outer disk.
Conclusions. We conclude that, in hybrid pebble-planetesimal scenarios, the late accretion of planetesimals is a critical factor in the giant planet formation process and that inward migration is more efficient for planets in increasingly pebble-dominated disks. We expect a reduced occurrence rate of giant planets in planet formation models that take the accretion of pebbles and planetesimals into account.