bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evaluation of the analytical performance of three chemiluminescence serological assays for detecting anti-SARS-CoV-2 antibodies
Authors: Lo Sasso Bruna , Agnello Luisa , Giglio Rosaria Vincenza , Scazzone Concetta , Massa Davide , Ciaccio Anna Maria , Gambino Caterina Maria , Vidali Matteo , Ciaccio Marcello 
Published: October 2022

AbstractThe serology surveillance of SARS-CoV-2 antibodies represents a useful tool for monitoring protective immunity in the population. We compared the performance of three SARS-CoV-2 antibody serological immunoassays in 600 vaccinated subjects after the BNT162b2 mRNA COVID-19 vaccine. All serum samples were evaluated by three different immunoassays for detecting anti-SARS-COV-2 antibodies. All SARS-CoV-2 antibody serological immunoassays could detect, when present, a post-vaccine humoral immune response. Median (interquartile range, IQR) anti-S-RBD IgG, Access SARS-CoV-2 IgG (1st IS) and Access SARS-CoV-2 IgG II levels of the subjects investigated were, respectively, 687 BAU/mL (131–2325), 419 IU/mL (58–1091) and 104 AU/mL (14–274). By studying a cohort of unvaccinated subjects, without previous COVID-19 infection, we found a high specificity for all methods. A high correlation was found between IgG titres. Considering the kinetics of subjects with multiple doses, we observed that percentage decreasing gradients were comparable across methods. Our results suggest that all the SARS-CoV-2 antibody serological immunoassays evaluated in this study are suitable for monitoring IgG titers over time. This study contributes to a better understanding of antibody response in vaccinated subjects using some currently available assays.
Preclinical Alzheimer’s dementia: a useful concept or another dead end?
Authors: Mark Ruth E. , Brehmer Yvonne 
Published: October 2022

AbstractThe term, preclinical dementia, was introduced in 2011 when new guidelines for the diagnosis of Alzheimer’s dementia (AD) were published. In the intervening 11 years, many studies have appeared in the literature focusing on this early stage. A search conducted in English on Google Scholar on 06.23.2022 using the term “preclinical (Alzheimer’s) dementia” produced 121, 000 results. However, the label is arguably more relevant for research purposes, and it is possible that the knowledge gained may lead to a cure for AD. The term has not been widely adopted by clinical practitioners. Furthermore, it is still not possible to predict who, after a diagnosis of preclinical dementia, will go on to develop AD, and if so, what the risk factors (modifiable and non-modifiable) might be. This Review/Theoretical article will focus on preclinical Alzheimer’s dementia (hereafter called preclinical AD). We outline how preclinical AD is currently defined, explain how it is diagnosed and explore why this is problematic at a number of different levels. We also ask the question: Is the concept ‘preclinical AD’ useful in clinical practice or is it just another dead end in the Holy Grail to find a treatment for AD? Specific recommendations for research and clinical practice are provided.
Implementation and Validation of an Algebraic Wall Model for LES in Nek5000
Authors: Gillyns Emmanuel , Buckingham Sophia , Winckelmans Grégoire 
Published: October 2022

AbstractTurbulent flows are most often wall-bounded, rendering the treatment of the wall essential. In this work, the near-wall layer is modelled in large eddy simulations which enables simulating high Reynolds number flows. An algebraic wall model has been implemented in the spectral element code Nek5000. It consists of an approximate boundary condition that relates the wall shear stress to the velocity measured close to the wall, on the upper edge of the first spectral element. The wall shear stress model approximates the law of the wall for hydraulically smooth cases. The model is applied to channel flow cases at $$Re_{\tau }=1000$$

R

e
τ

=
1000

and at $$Re_{\tau }=5200$$

R

e
τ

=
5200

. The wmLES results obtained with the present implementation are seen to compare very well with those of reference direct numerical simulations in the resolved region. They also remain remarkably close to the reference results for a large part of the under-resolved region; which is not necessarily the case when using low order implementations and even other types of high order discretizations, as found in the literature. Various parameters are studied such as the time averaging, the height of the near wall under-resolved element, and the mesh requirements. The obtained results indicate that accurate results can be obtained with Nek5000 at a reduced cost thanks to this newly implemented wmLES model. This work provides the necessary guidelines for simple flows, and it will serve as a first basis for simulating more complex flows at high Reynolds numbers.
Consistency of Eye Coloration Across Different Relationship Partners
Authors: Newman Amy V. , Pollet Thomas V. , McCarty Kristofor , Neave Nick , Saxton Tamsin K. 
Published: October 2022

AbstractStudies have indicated that people are attracted to partners who resemble themselves or their parents, in terms of physical traits including eye color. We might anticipate this inclination to be relatively stable, giving rise to a sequential selection of similar partners who then represent an individual’s “type”. We tested this idea by examining whether people’s sequential partners resembled each other at the level of eye color. We gathered details of the eye colors of the partners of participants (N = 579) across their adult romantic history (N = 3250 relationships), in three samples, comprising two samples which made use of self-reports from predominantly UK-based participants, and one which made use of publicly available information about celebrity relationship histories. Recorded partner eye colors comprised black (N = 39 partners), dark brown (N = 884), light brown (N = 393), hazel (N = 224), blue (N = 936), blue green (N = 245), grey (N = 34), and green (N = 229). We calculated the proportion of identical eye colors within each participant’s relationship history, and compared that to 100,000 random permutations of our dataset, using t-tests to investigate if the eye color of partners across an individual’s relationship history was biased relative to chance (i.e., if there was greater consistency, represented by higher calculated proportions of identical eye colors, in the original dataset than in the permutations). To account for possible eye color reporting errors and ethnic group matching, we ran the analyses restricted to White participants and to high-confidence eye color data; we then ran the analyses again in relation to the complete dataset. We found some limited evidence for some consistency of eye color across people’s relationship histories in some of the samples only when using the complete dataset. We discuss the issues of small effect sizes, partner-report bias, and ethnic group matching in investigating partner consistency across time.
Disentangling the Long-term Effects of Divorce Circumstances on Father–Child Closeness in Adulthood: A Mediation Analysis
Authors: Spaan Juul , van Gaalen Ruben , Kalmijn Matthijs 
Published: October 2022

AbstractMany studies have shown that the relationship between nonresidential fathers and their children in youth has a lasting influence on their relationship in adulthood. Comparatively less is known about the process through which divorce affects father–child relationships. We assess if and how the divorce circumstances of interparental conflict, the presence of new partners, and geographical distance between parents affect nonresidential father–child closeness in adulthood. Using a path model, we test whether father–adult child closeness is mediated by fathers’ involvement after divorce. The results of this study demonstrate that the level of interparental conflict and the presence of a fathers’ new partner after the divorce negatively affect the closeness between fathers and children in adulthood. Our mediation analysis demonstrates that both the effects of interparental conflict and new partnerships on closeness are partially mediated by father involvement and contact frequency during childhood. In other words, it is partly through the negative effect that interparental conflict and new partners have on fathers’ involvement that fathers and children become less close later in life. Our study highlights the importance of disentangling the effects of different factors associated with divorce when examining nonresidential father–child relationships.
Genetic and genomic approaches for breeding rust resistance in wheat
Authors: Baranwal Deepak 
Published: October 2022

AbstractWheat rusts are considered major biotic stresses due to immense yield losses incurred by the rust pathogens. Continuous incursions and evolution among populations of rust pathogen have challenged several resistance genes deployed in wheat mega-varieties. A substantial amount of wheat production is being saved by rust resistance wheat varieties. Breeding for rust resistance aimed to transfer potential genes in wheat elite lines and discover novel alleles to diversify resistance gene stock for future wheat breeding. This class of research was initiated worldwide after the discovery of mendelian genetics. Over a century, several genetic and genomic approaches were discovered and subsequently applied in wheat research to better understand the nature of rust pathogens and accordingly deployed major and minor rust resistant genes in combination in wheat varieties. Over 240 rust resistance genes have been catalogued and several alleles/QTL have been reported. Various statistical tools and consensus maps have been designed to precisely allocate novel alleles, as well as known genes on the wheat physical map. With the advancement in genomics and next generation sequencing (NGS) technology, more than 20 rust resistance genes have been cloned in the last two decades. The mutational genomics approach was found competitive and parallel to modern NGS technology in isolating rust resistance loci. In this review, evolutionary trends of rust pathogens, source of rust resistance genes, methodology used in genetic and association mapping studies and available cutting-edge techniques to isolate disease resistance genes have been summarised and discussed.
On the Implementation of an Adaptive Multirate Framework for Coupled Transport and Flow
Authors: Bruchhäuser Marius Paul , Köcher Uwe , Bause Markus 
Published: October 2022

AbstractThis paper presents a multirate in time approach for coupled flow and transport problems combined with goal-oriented error control based on the Dual Weighted Residual (DWR) method. The focus is on the implementation of the multirate concept regarding different time scales for the underlying subproblems. Key ingredients are an arbitrary degree discontinuous Galerkin time discretization, an a posteriori error representation for the transport problem coupled with flow and the concept of space-time slabs based on tensor-product spaces. From the latter, a space-time mesh adaptation with highly economical grids is developed. The performance of the approach is studied carefully by numerical convergence examples as well as an example of physical interest for convection-dominated transport.
Infrared Thermal Imaging-Based Turbine Blade Crack Classification Using Deep Learning
Authors: Jaeger Benedict E. , Schmid Simon , Grosse Christian U. , Gögelein Anian , Elischberger Frederik 
Published: October 2022

AbstractNon-destructive testing is widely applied for the detection and identification of defects in turbine blades of modern aircraft engines. Cracks in turbine blades can affect the turbine performance and pose a risk to safety and service life. For Original Equipment Manufacturers it is, therefore, essential to be able to identify all defects. Heat flow thermography offers, compared to the often used penetrant testing, the potential to improve the detection of defects in turbine blades and is contact-free, reproducible, quick to apply, and can be automated. With induction (heat flow) thermography, it is even possible to detect cracks that lie below the surface and therefore are not externally visible. However, manual inspection of thermography images is very time-consuming. By automating the image classification procedure with a deep learning technique, the speed and accuracy of the classification can be improved over a manually performed classification. The development objective of this AI application is expected to support and assist the highly skilled and experienced inspection specialists in the medium term. Our solution is based on convolutional neural networks. Several challenges of the AI training process, including data imbalance, a small dataset, and extremely small cracks in large images are addressed.
A system pharmacology Boolean network model for the TLR4-mediated inflammatory response in early sepsis
Authors: Liu Feiyan , Aulin Linda B. S. , Kossen Sebastiaan S. A. , Cathalina Julius , Bremmer Marlotte , Foks Amanda C. , van der Graaf Piet H. , Moerland Matthijs , van Hasselt Johan G. C. 
Published: October 2022

AbstractSepsis is a life-threatening condition driven by the dysregulation of the host immune response to an infection. The complex and interacting mechanisms underlying sepsis remain not fully understood. By integrating prior knowledge from literature using mathematical modelling techniques, we aimed to obtain a deeper mechanistic insight into sepsis pathogenesis and to evaluate promising novel therapeutic targets, with a focus on Toll-like receptor 4 (TLR4)-mediated pathways. A Boolean network of regulatory relationships was developed for key immune components associated with sepsis pathogenesis after TLR4 activation. Perturbation analyses were conducted to identify therapeutic targets associated with organ dysfunction or antibacterial activity. The developed model consisted of 42 nodes and 183 interactions. Perturbation analyses suggest that over-expression of tumour necrosis factor alpha (TNF-α) or inhibition of soluble receptor sTNF-R, tissue factor, and inflammatory cytokines (IFN-γ, IL-12) may lead to a reduced activation of organ dysfunction related endpoints. Over-expression of complement factor C3b and C5b led to an increase in the bacterial clearance related endpoint. We identified that combinatory blockade of IFN-γ and IL-10 may reduce the risk of organ dysfunction. Finally, we found that combining antibiotic treatment with IL-1β targeted therapy may have the potential to decrease thrombosis. In summary, we demonstrate how existing biological knowledge can be effectively integrated using Boolean network analysis for hypothesis generation of potential treatment strategies and characterization of biomarker responses associated with the early inflammatory response in sepsis.
Enantiopure β-isocyano-boronic esters: synthesis and exploitation in isocyanide-based multicomponent reactions
Authors: Manenti Marco , Gusmini Simone , Lo Presti Leonardo , Molteni Giorgio , Silvani Alessandra 
Published: October 2022

AbstractVarious boron-containing isocyanides have been efficiently synthesized from the corresponding enantiopure β-substituted β-amino boronic acid pinacol esters, without need for protecting group interconversion, through a two-step, purification-free procedure. They were employed in a variety of isocyanide-based multicomponent reactions, proving to be reliable components for all of them and allowing the efficient synthesis of unprecedented, boron-containing peptidomimetics and heteroatom-rich small molecules, including biologically relevant cyclic boronates. Jointing together the β-amido boronic acid moiety, deriving from the isocyanide component, with prominent pharmacophoric rings emerging from the multicomponent process, a successful application of the molecular hybridization concept could be realized.
Graphical abstract
Tissue P systems with evolutional communication rules with two objects in the left-hand side
Authors: Orellana-Martín David , Valencia-Cabrera Luis , Song Bosheng , Pan Linqiang , Pérez-Jiménez Mario J. 
Published: October 2022

AbstractIn the framework of Membrane Computing, several efficient solutions to computationally hard problems have been given. To find new borderlines between families of P systems that can solve them and the ones that cannot is an important task to tackle the P versus NP problem. Adding syntactic and/or semantic ingredients can mean passing from non-efficiency to presumed efficiency. Here, we try to get narrow frontiers, setting the stage to adapt efficient solutions from a family of P systems to another one. In order to do that, a solution to the problem is given by means of a family of tissue P systems with evolutional symport/antiport rules and cell separation with the restriction that both the left-hand side and the right-hand side of the rules have at most two objects; that is, with recognizer P systems from $${\mathcal {TSEC}}(2, 2)$$

TSEC
(
2
,
2
)

. This result improves a previous one, when 3 objects could be used in the left-hand side of the evolutional communication rules
In Silico Dosimetry Study of Tc99m-Tetrofosmin in Children Using a Novel PBPK Model in Humans Built from SPECT Imaging Data
Authors: Kaikousidis Christos , Dokoumetzidis Aristides 
Published: October 2022

Abstract
Purpose
The aim of this work is to develop a Physiologically Based Pharmacokinetic model (PBPK) for the radiopharmaceutical Tc99m-Tetrofosmin in humans, from literature SPECT imaging data, to carry out in-silico dosimetry studies in children and extrapolate dosing.

Methods
A whole body PBPK model was developed from literature data from humans of Tc99m-Tetrofosmin tissue distribution. A data driven approach to estimate partition coeffects, permeability parameters and clearances was carried out, while some parameters were determined using a standard in silico PBPK method. Paediatric PK data for all tissues were simulated by changing the physiological parameters from the adult to paediatric values. Absorbed and effective doses for children of all ages were calculated using S-values from literature of Tc99m that have been computed from anthropomorphic phantoms.

Results
Using the results from each tissue, satisfactory goodness-of-fit was achieved, assessed by visual inspection and a coefficient of determination of R2 = 0.965 while all estimated parameters had good standard errors. Paediatric simulations of Tetrofosmin distribution showed that paediatric profiles are not very different to the those of adults. The effective doses per unit of administered activity for 15 yo, 10 yo, 5 yo and 1 yo children were calculated to be 1.2, 1.7, 2.6 and 4.8 times higher, respectively than the adult value. Based on these calculations maximum administered activity scale more than proportionately to body weight.

Conclusions
A PBPK model of tetrofosmin in adults has been developed from SPECT imaging data and was extrapolated to conduct in-silico dosimetry studies in children of all ages.
Affine-mapping based variational ensemble Kalman filter
Authors: Wen Linjie , Li Jinglai 
Published: October 2022

AbstractWe propose an affine-mapping based variational ensemble Kalman filter for sequential Bayesian filtering problems with generic observation models. Specifically, the proposed method is formulated as to construct an affine mapping from the prior ensemble to the posterior one, and the affine mapping is computed via a variational Bayesian formulation, i.e., by minimizing the Kullback–Leibler divergence between the transformed distribution through the affine mapping and the actual posterior. Some theoretical properties of resulting optimization problem are studied and a gradient descent scheme is proposed to solve the resulting optimization problem. With numerical examples we demonstrate that the method has competitive performance against existing methods.
On the Suitability of NOx-Storage-Catalysts for Hydrogen Internal Combustion Engines and a Radio Frequency-Based NOx Loading Monitoring
Authors: Walter S. , Hagen G. , Koch D. , Geißelmann A. , Moos R. 
Published: October 2022

AbstractHydrogen combustion engines can contribute to CO2-free mobility. However, they produce NOx emissions, albeit only to an extremely small extent when operated very leanly. One approach to reduce these emissions even further is to use exhaust gas aftertreatment systems like NOx storage catalysts (NSC). So far, they have mainly been used in diesel or gasoline applications. This contribution shows that under conditions such as those prevailing in hydrogen engines, the NSC can achieve not only a higher storage capacity for nitrogen oxides (NOx) but also a higher conversion. To ensure permanently high conversion rates, the amount of stored NOx has to be monitored permanently to prevent NOx breakthroughs. Conventional NOx sensors may not be accurate enough due to the very low NOx emissions. The functionality of the radio frequency (RF) sensor, which enables a direct determination of the NOx loading, is demonstrated for operation under hydrogen conditions. Furthermore, the influence of rich exhaust gas on the RF signal, which is relevant for a correct NOx loading determination during regeneration, is analyzed.
Data-driven health deficit assessment improves a frailty index’s prediction of current cognitive status and future conversion to dementia: results from ADNI
Authors: Engvig Andreas , Maglanoc Luigi A. , Doan Nhat Trung , Westlye Lars T. ,   Alzheimer’s Disease Neuroimaging Initiative
Published: October 2022

AbstractFrailty is a dementia risk factor commonly measured by a frailty index (FI). The standard procedure for creating an FI requires manually selecting health deficit items and lacks criteria for selection optimization. We hypothesized that refining the item selection using data-driven assessment improves sensitivity to cognitive status and future dementia conversion, and compared the predictive value of three FIs: a standard 93-item FI was created after selecting health deficit items according to standard criteria (FIs) from the ADNI database. A refined FI (FIr) was calculated by using a subset of items, identified using factor analysis of mixed data (FAMD)-based cluster analysis. We developed both FIs for the ADNI1 cohort (n = 819). We also calculated another standard FI (FIc) developed by Canevelli and coworkers. Results were validated in an external sample by pooling ADNI2 and ADNI-GO cohorts (n = 815). Cluster analysis yielded two clusters of subjects, which significantly (pFDR < .05) differed on 26 health items, which were used to compute FIr. The data-driven subset of items included in FIr covered a range of systems and included well-known frailty components, e.g., gait alterations and low energy. In prediction analyses, FIr outperformed FIs and FIc in terms of baseline cognition and future dementia conversion in the training and validation cohorts. In conclusion, the data show that data-driven health deficit assessment improves an FI's prediction of current cognitive status and future dementia, and suggest that the standard FI procedure needs to be refined when used for dementia risk assessment purposes.