bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluating the contribution of plant metabolic pathways in the light to the ATP:NADPH demand using a meta-analysis of isotopically non-stationary metabolic flux analyses
Authors: Smith Kaila , Strand Deserah D. , Walker Berkley J.
Published: June 2024

Balancing the ATP: NADPH demand from plant metabolism with supply from photosynthesis is essential for preventing photodamage and operating efficiently, so understanding its drivers is important for integrating metabolism with the light reactions of photosynthesis and for bioengineering efforts that may radically change this demand. It is often assumed that the C3 cycle and photorespiration consume the largest amount of ATP and reductant in illuminated leaves and as a result mostly determine the ATP: NADPH demand. However, the quantitative extent to which other energy consuming metabolic processes contribute in large ways to overall ATP: NADPH demand remains unknown. Here, we used the metabolic flux networks of numerous recently published isotopically non-stationary metabolic flux analyses (INST-MFA) to evaluate flux through the C3 cycle, photorespiration, the oxidative pentose phosphate pathway, the tricarboxylic acid cycle, and starch/sucrose synthesis and characterize broad trends in the demand of energy across different pathways and compartments as well as in the overall ATP:NADPH demand. These data sets include a variety of species including Arabidopsis thaliana, Nicotiana tabacum, and Camelina sativa as well as varying environmental factors including high/low light, day length, and photorespiratory levels. Examining these datasets in aggregate reveals that ultimately the bulk of the energy flux occurred in the C3 cycle and photorespiration, however, the energy demand from these pathways did not determine the ATP: NADPH demand alone. Instead, a notable contribution was revealed from starch and sucrose synthesis which might counterbalance photorespiratory demand and result in fewer adjustments in mechanisms which balance the ATP deficit.
Molecular detection of Setaria tundra (Issaitshikoff & Rajewskaya, 1928) and Setaria cervi (Rudolphi, 1819) in red deer in Slovakia
Authors: Lazár Jozef , Šmigová Júlia , Šmiga Ľubomír , Berrilli Federica , Lazár Peter , Čurlík Ján , Papajová Ingrid
Published: June 2024

Filaroid nematodes Setaria tundra (Issaitshikoff & Rajewskaya, 1928) and Setaria cervi (Rudolphi, 1819) are internal parasites from family Onchocercidae with occurrence in the northern hemisphere. They have a considerably wide range of final host, including many species of family Cervidae. Intermediate hosts and vectors at the same time, are represented by the several mosquito species, mostly of genus Aedes. Infection of Setaria is relatively harmless and especially in wild cervids usually pass unnoticed. Although in some cases it can induce peritonitis which might be a life threatening condition.

This study was determined to reveal the presence of helminths Setaria tundra and Setaria cervi in red deer (Cervus elaphus) in Slovakia. The parasites were identified morphologically and genetically, based on the sequences of a fragment of the mitochondrial cytochrome c oxidase subunit 1 (cox1) gene. For this purpose we used partial results of our longer parasitological monitoring realized in one particular hunting area located in eastern Slovakia, near the city of Košice. A total of 60 red deer individuals were tested, of which one was found to be infected with Setaria tundra (prevalence of 1.7%) and four were detected to be infected with Setaria cervi (prevalence 6.7%). The intensity of infection was very low, only one specimen of Setaria spp. in each positive animal.
Immunomodulatory properties of chicken cathelicidin-2 investigated on an ileal explant culture
Authors: Mátis Gábor , Tráj Patrik , Hanyecz Viktória , Mackei Máté , Márton Rege Anna , Vörösházi Júlia , Kemény Ágnes , Neogrády Zsuzsanna , Sebők Csilla
Published: June 2024

As the threat posed by antimicrobial resistance grows more crucial, the development of compounds that can replace antibiotics becomes increasingly vital. Chicken cathelicidin-2 (Cath-2) belongs to the group of Host Defense Peptides (HDPs), which could provide a feasible solution for the treatment of gastrointestinal infections in poultry. It is a small peptide produced by the heterophil granulocytes of chickens as part of the innate immune response, and its immunomodulatory activity has already been demonstrated in several cell types. In this study, the effects of Cath-2 on the intestinal immune response were examined using ileal explant cultures isolated from chicken. Regarding our results, Cath-2 displayed a potent anti-inflammatory effect as it alleviated the LTA-caused elevation of interleukin (IL)-6 and IL-2 concentrations, and that of the IFN-γ/IL-10 ratio, furthermore, it increased the concentration of IL-10, alleviating the LTA-evoked decreased level of the anti-inflammatory cytokine. Moreover, when applied alone, it elevated the concentrations of IL-6, CXCLi2, and IL-2, providing evidence of its complex immunomodulatory mechanisms. In summary, Cath-2 was able to modulate the immune response of the intestinal wall not only by reducing pro-inflammatory cytokine release, but also through immune stimulation, demonstrating that it has the ability to improve innate immunity via a complex mechanism that may make it a suitable candidate for the control of intestinal infections.
Assessing alternative lake management actions for climate change adaptation
Authors: Regev Shajar , Carmel Yohay , Gal Gideon
Published: June 2024

Lake management actions are required to protect lake ecosystems that are being threatened by climate change. Freshwater lakes in semiarid regions are of upmost importance to their region. Simulations of the subtropical Lake Kinneret project that rising temperatures will cause change to phytoplankton species composition, including increased cyanobacteria blooms, endangering lake ecosystem services. Using lake ecosystem models, we examined several management actions under climate change, including two alternatives of desalinated water introduction into the lake, hypolimnetic water withdrawal, watershed management changes and low versus high lake water level. To account for prediction uncertainty, we utilized an ensemble of two 1D hydrodynamic—biogeochemical lake models along with 500 realizations of meteorological conditions. Results suggest that supplying desalinated water for local use, thus releasing more natural waters through the Jordan River, increasing nutrient flow, may reduce cyanobacteria blooms, mitigating climate change effects. However, these results are accompanied by considerable uncertainty.
IQB und SWK und ihr Beitrag zur Reform der Grundschule – Befindet sich die evidenzbasierte Reform in der Krise oder führt sie aus ihr heraus?
Authors: Eckermann Torsten
Published: June 2024

Am Beispiel der IQB-Bildungstrend 2021 wird die Rolle des nationalen Bildungsmonitorings für das Initiieren von Reformen untersucht. Entfaltet wird die These, dass sich das IQB nicht allein als Datenlieferant begreift, sondern gemeinsam mit dem Beratungsgremium (SWK) als Reformakteur in Erscheinung tritt. Die Analyse des anvisierten Reformprogramms legt nahe, dass die Maßnahmen einer evidence-based-policy folgen. Es wird eine Expansion des Monitorings über die verschiedenen Bildungsetappen (von frühkindlicher Bildung bis zur Lehrkräfteprofessionalisierung) angestrebt. Für die Grundschulforschung bieten die Reformabsichten wichtige Impulse und Diskussionsanstöße. Sie sind zugleich einer theoretisch und empirisch informierten Analyse, insbesondere im Hinblick auf nicht-intendierte Nebenfolgen, zu unterziehen. Die Reform strebt eine disparitätsmindernde Wirkung der Grundschule an und imaginiert einen zentralen Hebel (Evidenz, Diagnostik, Standardisierung) und eine pädagogische Monokultur. Unterstellt wird eine Homogenität (alle Kinder profitieren von mehr Diagnostik und Testung). Entgegen der Intention zur Verringerung des Anteils an „Risikokinder“ beizutragen, besteht jedoch die Gefahr ungewollt mehr „Risikokinder“ zu produzieren. Damit läuft die anvisierte Reform Gefahr, die eigentliche „Risikogruppe“ aus dem Auge zu verlieren, die begründet Anlass für Reformen gibt.
Numerische Kompetenzen tauber Schulanfänger_innen in Deutscher Gebärdensprache (DGS)
Authors: Werner Viktor , Hänel-Faulhaber Barbara
Published: June 2024

Zusammenfassung: Hintergrund: Taube Kinder sind aufgrund von heterogenen Spracherfahrungen zum Zeitpunkt des Schuleintritts besonders gefährdet, Entwicklungsverzögerungen bei den numerischen Basiskompetenzen aufzuweisen. Für die Erkennung dieser ist folglich eine frühzeitige Diagnostik vorschulischer numerischer Fähigkeiten in Deutscher Gebärdensprache (DGS) notwendig. Methode: In der vorliegenden Studie wurde ein Test zu mathematischen Basiskompetenzen in DGS übersetzt und an 31 tauben Schulanfänger_innen (5;6–7;9 Jahre) evaluiert. Ergebnisse: Die ersten Werte in Bezug auf die Itemschwierigkeiten und Gütekriterien des in DGS übersetzten MBK 0 entsprechen bei den native signers (taube Kinder tauber Eltern) größtenteils denen des MBK 0. Bestimmte Aufgaben zur Zahlenfolge, zum Benennen von zweiziffrigen Zahlen und zu den Rechengeschichten konnten im Vergleich zu den Normwerten häufiger korrekt gelöst werden. Bei den Gruppenergebnissen erzielten native signers signifikant bessere Ergebnisse als late signers (taube Kinder hörender Eltern und mit verzögertem Gebärdensprachzugang) und weisen keine Unterschiede zur Altersnorm auf. Diskussion: Die frühe Spracherfahrung in einem gebärdensprachlichen Elternhaus unterstützt die Entwicklung numerischer Kompetenzen. Bei bestimmten Aufgabentypen auftretende Differenzen müssen unter Berücksichtigung der modalitätsspezifischen Eigenschaften der DGS diskutiert werden.
Community Involvement and Mental Health in Russian LGBT People
Authors: Kranz Dirk , Arontschik Nadeshda , Osin Evgeny N.
Published: June 2024

Abstract: Introduction: This study examined the sources and factors of resilience in Russian sexual and gender minorities. We hypothesized that, through their involvement in the lesbian, gay, bisexual, and transgender (LGBT) community (source of resilience), LGBT people establish friendships that provide them with social support (factor of resilience), which in turn should contribute to their mental health. Method: The study sample consisted of 1,127 young and middle-aged LGBT adults (18 to 50 years) from Russia. We collected the data online and anonymously. Results: Partial mediation could be confirmed. LGBT people who were involved in “their” community reported more social support from friends, which partially mediated the positive association between community involvement and mental health. The mediation remained significant when we controlled for demographics and outness as potential covariates. Additional analyses showed that the present sample reported lower mental health but not less social support than Russian nonminority samples recruited in previous research. Conclusion: Our study underlines the importance of the LGBT community in times of increasing stigmatization of sexual and gender minorities.
Cloud Responses to Abrupt Solar and CO2 Forcing: 2. Adjustment to Forcing in Coupled Models
Authors: Aerenson T. , Marchand R. , Zhou C.
Published: June 2024

In this paper, we examine differences in cloud adjustments (often called rapid adjustments) that occur as a direct result of abruptly increasing the solar constant by 4% or abruptly quadrupling of atmospheric CO2. In doing so, we devise a novel method for calculating the cloud adjustments for the abrupt solar forcing simulations that uses differences between coupled model simulations with abrupt solar and CO2 forcing, in combination with uncoupled, atmosphere‐only, abrupt CO2 forced experiments that have prescribed sea‐surface temperature. Our main findings are that (a) there are substantial differences in the responses of stratocumulus and cumulus clouds to solar and CO2 forcing, which follow the differences in the direct radiative effect that solar and CO2 forcing have at cloud top, and (b) there are differences in the adjustment of the average optical depth of high clouds to solar and CO2 forcing that we speculate are driven by the differences in the vertical profile of radiative heating and differences in the pattern of sea‐surface temperature change (for a fixed global mean temperature). These cloud adjustments contribute significantly to the total net cloud radiative effect, even after 150 years of simulation.
From Disorder to Order: Inheritance of Magnetic Remanence in Tetrataenite‐Bearing Meteorites From Multi‐Phase Micromagnetic Modeling
Authors: Devienne José A. P. M. , Berndt Thomas A. , Williams Wyn , Chen Shichu
Published: June 2024

An increasing amount of evidence suggests that the tetrataenite‐bearing cloudy zones (CZ) in iron and stony‐iron meteorites can preserve magnetic records of ancient magnetic activity of their parent bodies over solar system timescales. Tetrataenite islands in the CZ are nanometer‐sized (<200 nm) crystals that usually form through ordering from precursor taenite islands upon extremely slow cooling through 320°C. Recent micromagnetic models have shown that such precursor taenite islands form highly thermally stable single‐domain (SD) or single‐vortex states (SV). In this work we employ a 3D finite element multi‐phase micromagnetic modeling to show that tetrataenite inherits the magnetic remanence of taenite precursor when it forms over underlying SD states. When taenite forms SV states, however, tetrataenite resets the precursor magnetization and records a new remanence through chemical ordering at 320°C. We further assess the thermal stability of tetrataenite islands. We show that in cases where tetrataenite inherits the domain states of its precursor taenite, the origin of the remanence can be up to ∼105 years older than previously thought in fast‐cooled meteorites, and ∼1–≳6 Myr in slowly cooled meteorites. It indicates, therefore, that different regions across slowly cooled CZ record distinct stages of planetary formation.
A Pressure Projection Scheme With Near‐Spectral Accuracy for Nonhydrostatic Flow in Domains With Open Boundaries
Authors: Winters K. B. , Claret Mariona , Lelong M.‐Pascale , Ourmières Yann
Published: June 2024

We describe a pressure projection scheme for the simulation of incompressible flow in cubic domains with open boundaries based on fast Fourier transforms. The scheme is implemented in flow_solve, a numerical code designed for process studies of rotating, density‐stratified flow. The main algorithmic features of the open‐boundary code are the near‐spectral accuracy of the discrete differentiation and a dynamic two‐dimensional domain decomposition that scales efficiently to large numbers of processors. The simulated flows are not required to be periodic or to satisfy symmetry conditions at the open boundaries owing to the use of mixed series expansions combining cosine and singular Bernoulli polynomial basis functions. These expansions facilitate the imposition of inhomogeneous boundary conditions and allow the code to be used for offline, one‐way nesting within an arbitrarily embedded subdomain of a larger scale simulation. The projection scheme is designed to exploit a simple and powerful numerical engine: inversion of Poisson's equation with homogeneous Neumann boundary conditions using fast cosine transforms. Here, we describe the mathematical transformations used to accommodate the imposition of space‐ and time‐varying boundary conditions. The utility of the approach for process studies and for nesting within submesoscale‐resolving ocean models is demonstrated with simulations of wind‐driven near‐inertial waves in the upper ocean.
Validation of Simulated Statistical Characteristics of Magnetosphere‐Ionosphere Coupling in Global Geospace Simulations Over an Entire Carrington Rotation
Authors: Yin Qianfeng , Pham Kevin H. , Chen Junjie , Zhang Binzheng
Published: June 2024

We study the statistical features of magnetosphere‐ionosphere (M‐I) coupling using a two‐way M‐I model, the GT configuration of the Multiscale Atmosphere Geospace Environment (MAGE) model. The M‐I coupling characteristics, such as field‐aligned current, polar cap potential, ionospheric Joule heating, and downward Alfvénic Poynting flux, are binned according to the interplanetary magnetic field clock angles over an entire Carrington Rotation event between 20 March and 16 April 2008. The MAGE model simulates similar distributions of field‐aligned currents compared to empirical Weimer/AMPS models and Iridium observations and reproduces the Region 0 current system. The simulated convection potential agrees well with the Weimer empirical model and displays consistent two‐cell patterns with SuperDARN observations, which benefit from more extensive data sets. The Joule heating structure in MAGE is generally consistent with both empirical Cosgrove and Weimer models. Moreover, our model reproduces Joule heating enhancements in the cusp region, as presented in the Cosgrove model and observations. The distribution of the simulated Alfvénic Poynting flux is consistent with that observed by the FAST satellite in the dispersive Alfvén wave regime. These M‐I coupling characteristics are also binned by the Kp indices, indicating that the Kp dependence of these patterns in the M‐I model is more effective than the empirical models within the Carrington Rotation. Furthermore, the MAGE simulation exhibits an improved M‐I current‐voltage relation that closely resembles the Weimer model, suggesting that the updated global model is significantly improved in terms of M‐I coupling.
PlanetMag: Software for Evaluation of Outer Planet Magnetic Fields and Corresponding Excitations at Their Moons
Authors: Styczinski M. J. , Cochrane C. J.
Published: June 2024

Spacecraft magnetic field measurements are able to tell us much about the planets' interior dynamics, composition, and evolutionary timeline. Magnetic fields also serve as the source for passive magnetic sounding of moons. Time‐varying magnetic fields experienced by the moons, due to relative planetary motion, interact electrically with conductive layers within these bodies (including salty subsurface oceans) to produce induced magnetic fields that are measurable by nearby, magnetometer‐equipped spacecraft. Many factors influence the character of the induced field, including the precise amplitude and phase of the time‐varying field, known as the excitation or driving field and represented by excitation moments. In this work, we present an open‐source Matlab software package named PlanetMag that features calculation of planetary magnetic field models available in the literature at arbitrary positions and times. The implemented models enable simultaneous inversion of the excitation moments across a range of oscillation frequencies using linear least‐squares methods and ephemeris data with the SPICE toolkit. Here we summarize the available magnetic field models and their associated coordinate systems. Precisely determined excitation moments are a critical input to forward models of global induced fields. Our results serve as a prerequisite to any precise comparison to spacecraft data for magnetic sounding investigation of giant planet moons—connecting the induced magnetic field to a moon's interior requires accurate representation of the oscillating excitation field. We calculate complex excitation moments relative to the J2000 epoch and share the results as ASCII tables compatible with related software packages intended for induction response calculations.
Did Short‐Term Preseismic Crustal Deformation Precede the 2011 Great Tohoku‐Oki Earthquake? An Examination of Stacked Tilt Records
Authors: Hirose Hitoshi , Kato Aitaro , Kimura Takeshi
Published: June 2024

The detection of preslip, occurring hours to days before a large earthquake, using geodetic measurements has been a major focus in earthquake prediction research. A recent study claims to have detected a preseismic signal interpreted as accelerating slip near the hypocenter of the 2011 great Tohoku‐oki earthquake, starting approximately 2 hr before the mainshock. This claim is based on a stacking procedure using GNSS (Global Navigation Satellite System) data. However, a follow‐up study demonstrated that the signal disappeared when specific GNSS noise was corrected. Here we utilize tiltmeter records, independent on GNSS, to check whether the claimed preseismic signal is detected using a similar stacking procedure. Our results show no acceleration‐like deformation from 2 hr before the mainshock. This indicates that no precursory slip exceeded the noise level of the tilt data, and if any preslip occurred, it was less than 5.0 × 1018 Nm in seismic moment.
Molecular insights into regulatory RNAs in the cellular machinery
Authors: Yang Sumin , Kim Sung-Hyun , Yang Eunjeong , Kang Mingon , Joo Jae-Yeol
Published: June 2024

It is apparent that various functional units within the cellular machinery are derived from RNAs. The evolution of sequencing techniques has resulted in significant insights into approaches for transcriptome studies. Organisms utilize RNA to govern cellular systems, and a heterogeneous class of RNAs is involved in regulatory functions. In particular, regulatory RNAs are increasingly recognized to participate in intricately functioning machinery across almost all levels of biological systems. These systems include those mediating chromatin arrangement, transcription, suborganelle stabilization, and posttranscriptional modifications. Any class of RNA exhibiting regulatory activity can be termed a class of regulatory RNA and is typically represented by noncoding RNAs, which constitute a substantial portion of the genome. These RNAs function based on the principle of structural changes through cis and/or trans regulation to facilitate mutual RNA‒RNA, RNA‒DNA, and RNA‒protein interactions. It has not been clearly elucidated whether regulatory RNAs identified through deep sequencing actually function in the anticipated mechanisms. This review addresses the dominant properties of regulatory RNAs at various layers of the cellular machinery and covers regulatory activities, structural dynamics, modifications, associated molecules, and further challenges related to therapeutics and deep learning.
Mitochondria from osteolineage cells regulate myeloid cell-mediated bone resorption
Authors: Ding Peng , Gao Chuan , Zhou Jian , Mei Jialun , Li Gan , Liu Delin , Li Hao , Liao Peng , Yao Meng , Wang Bingqi , Lu Yafei , Peng Xiaoyuan , Jiang Chenyi , Yin Jimin , Huang Yigang , Zheng Minghao , Gao Youshui , Zhang Changqing , Gao Junjie
Published: June 2024

Interactions between osteolineage cells and myeloid cells play important roles in maintaining skeletal homeostasis. Herein, we find that osteolineage cells transfer mitochondria to myeloid cells. Impairment of the transfer of mitochondria by deleting MIRO1 in osteolineage cells leads to increased myeloid cell commitment toward osteoclastic lineage cells and promotes bone resorption. In detail, impaired mitochondrial transfer from osteolineage cells alters glutathione metabolism and protects osteoclastic lineage cells from ferroptosis, thus promoting osteoclast activities. Furthermore, mitochondrial transfer from osteolineage cells to myeloid cells is involved in the regulation of glucocorticoid-induced osteoporosis, and glutathione depletion alleviates the progression of glucocorticoid-induced osteoporosis. These findings reveal an unappreciated mechanism underlying the interaction between osteolineage cells and myeloid cells to regulate skeletal metabolic homeostasis and provide insights into glucocorticoid-induced osteoporosis progression.
A diamond-bearing core-mantle boundary on Mercury
Authors: Xu Yongjiang , Lin Yanhao , Wu Peiyan , Namur Olivier , Zhang Yishen , Charlier Bernard
Published: June 2024

Abundant carbon was identified on Mercury by MESSENGER, which is interpreted as the remnant of a primordial graphite flotation crust, suggesting that the magma ocean and core were saturated in carbon. We re-evaluate carbon speciation in Mercury’s interior in light of the high pressure-temperature experiments, thermodynamic models and the most recent geophysical models of the internal structure of the planet. Although a sulfur-free melt would have been in the stability field of graphite, sulfur dissolution in the melt under the unique reduced conditions depressed the sulfur-rich liquidus to temperatures spanning the graphite-diamond transition. Here we show it is possible, though statistically unlikely, that diamond was stable in the magma ocean. However, the formation of a solid inner core caused diamond to crystallize from the cooling molten core and formation of a diamond layer becoming thicker with time.
Direct in-situ imaging of electrochemical corrosion of Pd-Pt core-shell electrocatalysts
Authors: Shi Fenglei , Tieu Peter , Hu Hao , Peng Jiaheng , Zhang Wencong , Li Fan , Tao Peng , Song Chengyi , Shang Wen , Deng Tao , Gao Wenpei , Pan Xiaoqing , Wu Jianbo
Published: June 2024

Corrosion of electrocatalysts during electrochemical operations, such as low potential - high potential cyclic swapping, can cause significant performance degradation. However, the electrochemical corrosion dynamics, including structural changes, especially site and composition specific ones, and their correlation with electrochemical processes are hidden due to the insufficient spatial-temporal resolution characterization methods. Using electrochemical liquid cell transmission electron microscopy, we visualize the electrochemical corrosion of Pd@Pt core-shell octahedral nanoparticles towards a Pt nanoframe. The potential-dependent surface reconstruction during multiple continuous in-situ cyclic voltammetry with clear redox peaks is captured, revealing an etching and deposition process of Pd that results in internal Pd atoms being relocated to external surface, followed by subsequent preferential corrosion of Pt (111) terraces rather than the edges or corners, simultaneously capturing the structure evolution also allows to attribute the site-specific Pt and Pd atomic dynamics to individual oxidation and reduction events. This work provides profound insights into the surface reconstruction of nanoparticles during complex electrochemical processes.
Divergent evolution of sleep in Drosophila species
Authors: Joyce Michaela , Falconio Federica A. , Blackhurst Laurence , Prieto-Godino Lucia , French Alice S. , Gilestro Giorgio F.
Published: June 2024

Living organisms synchronize their biological activities with the earth’s rotation through the circadian clock, a molecular mechanism that regulates biology and behavior daily. This synchronization factually maximizes positive activities (e.g., social interactions, feeding) during safe periods, and minimizes exposure to dangers (e.g., predation, darkness) typically at night. Beyond basic circadian regulation, some behaviors like sleep have an additional layer of homeostatic control, ensuring those essential activities are fulfilled. While sleep is predominantly governed by the circadian clock, a secondary homeostatic regulator, though not well-understood, ensures adherence to necessary sleep amounts and hints at a fundamental biological function of sleep beyond simple energy conservation and safety. Here we explore sleep regulation across seven Drosophila species with diverse ecological niches, revealing that while circadian-driven sleep aspects are consistent, homeostatic regulation varies significantly. The findings suggest that in Drosophilids, sleep evolved primarily for circadian purposes. The more complex, homeostatically regulated functions of sleep appear to have evolved independently in a species-specific manner, and are not universally conserved. This laboratory model may reproduce and recapitulate primordial sleep evolution.
A comprehensive generalization of the Friendship Paradox to weights and attributes
Authors: Evtushenko Anna , Kleinberg Jon
Published: June 2024

The Friendship Paradox is a simple and powerful statement about node degrees in a graph. However, it only applies to undirected graphs with no edge weights, and the only node characteristic it concerns is degree. Since many social networks are more complex than that, it is useful to generalize this phenomenon, if possible, and a number of papers have proposed different generalizations. Here, we unify these generalizations in a common framework, retaining the focus on undirected graphs and allowing for weighted edges and for numeric node attributes other than degree to be considered, since this extension allows for a clean characterization and links to the original concepts most naturally. While the original Friendship Paradox and the Weighted Friendship Paradox hold for all graphs, considering non-degree attributes actually makes the extensions fail around 50% of the time, given random attribute assignment. We provide simple correlation-based rules to see whether an attribute-based version of the paradox holds. In addition to theory, our simulation and data results show how all the concepts can be applied to synthetic and real networks. Where applicable, we draw connections to prior work to make this an accessible and comprehensive paper that lets one understand the math behind the Friendship Paradox and its basic extensions.
Accelerating the design of lattice structures using machine learning
Authors: Gongora Aldair E. , Friedman Caleb , Newton Deirdre K. , Yee Timothy D. , Doorenbos Zachary , Giera Brian , Duoss Eric B. , Han Thomas Y.-J. , Sullivan Kyle , Rodriguez Jennifer N.
Published: June 2024

Lattices remain an attractive class of structures due to their design versatility; however, rapidly designing lattice structures with tailored or optimal mechanical properties remains a significant challenge. With each added design variable, the design space quickly becomes intractable. To address this challenge, research efforts have sought to combine computational approaches with machine learning (ML)-based approaches to reduce the computational cost of the design process and accelerate mechanical design. While these efforts have made substantial progress, significant challenges remain in (1) building and interpreting the ML-based surrogate models and (2) iteratively and efficiently curating training datasets for optimization tasks. Here, we address the first challenge by combining ML-based surrogate modeling and Shapley additive explanation (SHAP) analysis to interpret the impact of each design variable. We find that our ML-based surrogate models achieve excellent prediction capabilities (R2 > 0.95) and SHAP values aid in uncovering design variables influencing performance. We address the second challenge by utilizing active learning-based methods, such as Bayesian optimization, to explore the design space and report a 5 × reduction in simulations relative to grid-based search. Collectively, these results underscore the value of building intelligent design systems that leverage ML-based methods for uncovering key design variables and accelerating design.
Effects of switching from intravitreal injection of aflibercept to faricimab on ocular blood flow in patients with diabetic macular edema
Authors: Saima Yoshinari , Yokota Harumasa , Kushiyama Akifumi , Hanaguri Junya , Ohno Akira , Takase Koyo , Sugiyama Ruri , Muranaka Kimimasa , Yamagami Satoru , Nagaoka Taiji
Published: June 2024

We assessed the short-term effects of switching from intravitreal aflibercept (IVA) to intravitreal faricimab (IVF) on ocular blood flow in patients with treatment-resistant diabetic macular edema (DME). The medical records of 15 patients with DME who had received IVA injection ≥ 3 months before were retrospectively reviewed. The best-corrected visual acuity, central macular thickness (CMT) on optical coherence tomography, and mean blur rate (MBR) of all disc areas on laser speckle flowgraphy were measured before, 1 week after, and 4 weeks after IVA and IVF, respectively. The changes in visual acuity showed no significant difference after switching from IVA to IVF (P = 0.732). The mean CMT decreased significantly during the follow-up period (both P < 0.001). MBR showed no significant difference during the follow-up period (P = 0.26). However, it decreased significantly 4 weeks after IVF (P = 0.01) compared with the baseline value, but not 4 weeks after IVA (P = 0.074). A significant association was observed between decreased MBR and decreased CMT in patients who received IVF (correlation coefficient: 0.501, P = 0.005) but not in those who received IVA (P = 0.735). Thus, IVF maintained ocular blood flow reduction, although no significant differences in visual acuity and CMT changes were observed compared to IVA.
Dairy cows’ motivation to nurse their calves
Authors: Jensen Emma Hvidtfeldt , Bateson Melissa , Neave Heather W. , Rault Jean-Loup , Jensen Margit Bak
Published: June 2024

When weaning offspring, female mammals limit nursing opportunities. This study aimed to investigate whether imposing a gradual reduction in daily contact time, by separating cows from their calves as an attempt to stimulate weaning, reduced dairy cows’ motivation to nurse their calves. For seven weeks, 84 Holstein–Friesian cow-calf pairs were housed with either full-time (23 h contact/d), part-time (10 h contact/d), or no contact. In the following two weeks, half of full- and part-time pairs were subjected to reduced contact (50% of initial contact in week 8, 25% of initial contact in week 9), while the other half continued with unchanged contact. In weeks 8 and 9, cows’ motivation to obtain full contact to and opportunity to nurse their calves was measured using weighted push gates using a novel maximum price paid method providing an alternative choice to the cows to reduce frustration. Cows with reduced calf contact were more motivated than cows with unchanged contact; however, cows used the alternative choice less than expected. The results show that cows’ motivation for full calf contact and opportunity to nurse increases when daily calf contact is reduced, illustrating that dairy cows are motivated to continue nursing their 9- to 10-week-old calves.
Enhancing computer image recognition with improved image algorithms
Authors: Huang Lanqing , Yao Cheng , Zhang Lingyan , Luo Shijian , Ying Fangtian , Ying Weiqiang
Published: June 2024

Advances in computer image recognition have significantly impacted many industries, including healthcare, security and autonomous systems. This paper aims to explore the potential of improving image algorithms to enhance computer image recognition. Specifically, we will focus on regression methods as a means to improve the accuracy and efficiency of identifying images. In this study, we will analyze various regression techniques and their applications in computer image recognition, as well as the resulting performance improvements through detailed examples and data analysis. This paper deals with the problems related to visual image processing in outdoor unstructured environment. Finally, the heterogeneous patterns are converted into the same pattern, and the heterogeneous patterns are extracted from the fusion features of data modes. The simulation results show that the perception ability and recognition ability of outdoor image recognition in complex environment are improved.
C-reactive protein as robust laboratory value associated with prognosis in patients with stage III non-small cell lung cancer (NSCLC) treated with definitive radiochemotherapy
Authors: Richlitzki Cedric , Wiesweg Marcel , Metzenmacher Martin , Guberina Nika , Pöttgen Christoph , Hautzel Hubertus , Eberhardt Wilfried E. E. , Darwiche Kaid , Theegarten Dirk , Aigner Clemens , Bölükbas Servet , Schuler Martin , Stuschke Martin , Guberina Maja
Published: June 2024

To evaluate the prognostic value of biomarkers from peripheral blood obtained as routine laboratory assessment for overall survival in a cohort of stage III non-small cell lung cancer (NSCLC) patients treated with definitive radiochemotherapy at a high-volume cancer center. Seven blood biomarkers from 160 patients treated with definitive radiochemotherapy for stage III NSCLC were analyzed throughout the course treatment. Parameters were preselected using univariable and multivariable proportional hazards analysis and were assessed for internal validity using leave-one-out cross validation. Cross validated classifiers including biomarkers in addition to important clinical parameters were compared with classifiers containing the clinical parameters alone. An increased C-reactive protein (CRP) value in the final week of radiotherapy was found as a prognostic factor for overall survival, both as a continuous (HR 1.099 (1.038–1.164), p < 0.0012) as well as categorical variable splitting data at the median value of 1.2 mg/dl (HR 2.214 (1.388–3.531), p < 0.0008). In the multivariable analysis, the CRP value-maintained significance with an HR of 1.105 (1.040–1.173) and p-value of 0.0012. The cross validated classifier using CRP at the end of radiotherapy in addition to clinical parameters separated equally sized high and low risk groups more distinctly than a classifier containing the clinical parameters alone (HR = 2.786 (95% CI 1.686–4.605) vs. HR = 2.287 (95% CI 1.407–3.718)). Thus, the CRP value at the end of radiation therapy has successfully passed the crucial cross-validation test. The presented data on CRP levels suggests that inflammatory markers may become increasingly important during definitive radiochemotherapy, particularly with the growing utilization of immunotherapy as a consolidation therapy for stage III NSCLC.
Kidney cancer in the Middle East and North Africa region: a 30-year analysis (1990–2019)
Authors: Safiri Saeid , Hassanzadeh Kamaleddin , Ghaffari Jolfayi Amir , Mousavi Seyed Ehsan , Motlagh Asghari Kimia , Nejadghaderi Seyed Aria , Naghdi-Sedeh Nima , Noori Maryam , Sullman Mark J. M. , Collins Gary S. , Kolahi Ali-Asghar
Published: June 2024

Kidney cancer, a type of urogenital cancer, imposes a high burden on patients. Despite this, no recent research has evaluated the burden of this type of cancer in the Middle East and North Africa (MENA) region. This study explored the burden of kidney cancer from 1990 to 2019 according to age, sex and socio-demographic index (SDI). The Global Burden of Disease (GBD) 2019 data was utilized to estimate the incidence, death, and disability-adjusted life-years (DALYs) caused by kidney cancer. These estimates were reported as counts and as age-standardised rates with 95% uncertainty intervals (UIs). The estimated age-standardised incidence, mortality, and DALY rates of kidney cancer in 2019 were 3.2 (2.8–3.6), 1.4 (1.2–1.6), and 37.2 (32.0–42.6) per 100,000, respectively. Over the period from 1990 to 2019, these rates have increased by 98.0%, 48.9%, and 37.7%, respectively. In 2019, the United Arab Emirates, Qatar, and Lebanon had the largest age-standardised incidence, mortality, and DALY rates. The smallest age-standardised incidence rates were seen in Yemen, Afghanistan, and the Syrian Arab Republic. Additionally, the smallest age-standardised mortality and DALY rates were observed in the Syrian Arab Republic, Yemen, and Morocco. The highest incidence rates were found among individuals aged 75–79 in both males and females. In 2019, the MENA/Global DALY ratio exceeded one for females aged 5–19 age and males aged 5–14, compared to 1990age groups in males. The burden of kidney cancer consistently rose with increasing SDI levels from 1990 to 2019. The increasing burden of kidney cancer highlights the urgent need for interventions aimed at improving early diagnosis and treatment in the region.
Prediction of COD in industrial wastewater treatment plant using an artificial neural network
Authors: Çimen Mesutoğlu Özgül , Gök Oğuzhan
Published: June 2024

In this investigation, the modeling of the Aksaray industrial wastewater treatment plant was performed using artificial neural networks with various architectures in the MATLAB software. The dataset utilized in this study was collected from the Aksaray wastewater treatment plant over a 9-month period through daily records. The treatment efficiency of the plants was assessed based on the output values of chemical oxygen demand (COD) output. Principal component analysis (PCA) was applied to furnish input for the Feedforward Backpropagation Artificial Neural Networks (FFBANN). The model’s performance was evaluated using the Mean Squared Error (MSE), the Mean Absolute Error (MAE) and correlation coefficient (R2) parameters. The optimal architecture for the neural network model was determined through several trial and error iterations. According to the modeling results, the ANN exhibited a high predictive capability for plant performance, with an R2 reaching up to 0.9997 when comparing the observed and predicted output variables.
Development of a real-time cattle lameness detection system using a single side-view camera
Authors: Myint Bo Bo , Onizuka Tsubasa , Tin Pyke , Aikawa Masaru , Kobayashi Ikuo , Zin Thi Thi
Published: June 2024

Recent advancements in machine learning and deep learning have revolutionized various computer vision applications, including object detection, tracking, and classification. This research investigates the application of deep learning for cattle lameness detection in dairy farming. Our study employs image processing techniques and deep learning methods for cattle detection, tracking, and lameness classification. We utilize two powerful object detection algorithms: Mask-RCNN from Detectron2 and the popular YOLOv8. Their performance is compared to identify the most effective approach for this application. Bounding boxes are drawn around detected cattle to assign unique local IDs, enabling individual tracking and isolation throughout the video sequence. Additionally, mask regions generated by the chosen detection algorithm provide valuable data for feature extraction, which is crucial for subsequent lameness classification. The extracted cattle mask region values serve as the basis for feature extraction, capturing relevant information indicative of lameness. These features, combined with the local IDs assigned during tracking, are used to compute a lameness score for each cattle. We explore the efficacy of various established machine learning algorithms, such as Support Vector Machines (SVM), AdaBoost and so on, in analyzing the extracted lameness features. Evaluation of the proposed system was conducted across three key domains: detection, tracking, and lameness classification. Notably, the detection module employing Detectron2 achieved an impressive accuracy of 98.98%. Similarly, the tracking module attained a high accuracy of 99.50%. In lameness classification, AdaBoost emerged as the most effective algorithm, yielding the highest overall average accuracy (77.9%). Other established machine learning algorithms, including Decision Trees (DT), Support Vector Machines (SVM), and Random Forests, also demonstrated promising performance (DT: 75.32%, SVM: 75.20%, Random Forest: 74.9%). The presented approach demonstrates the successful implementation for cattle lameness detection. The proposed system has the potential to revolutionize dairy farm management by enabling early lameness detection and facilitating effective monitoring of cattle health. Our findings contribute valuable insights into the application of advanced computer vision methods for livestock health management.
Risk prediction of cholangitis after stent implantation based on machine learning
Authors: Zhao Rui , Gu Lin , Ke Xiquan , Deng Xiaojing , Li Dapeng , Ma Zhenzeng , Wang Qizhi , Zheng Hailun , Yang Yong
Published: June 2024

The risk of cholangitis after ERCP implantation in malignant obstructive jaundice patients remains unknown. To develop models based on artificial intelligence methods to predict cholangitis risk more accurately, according to patients after stent implantation in patients’ MOJ clinical data. This retrospective study included 218 patients with MOJ undergoing ERCP surgery. A total of 27 clinical variables were collected as input variables. Seven models (including univariate analysis and six machine learning models) were trained and tested for classified prediction. The model’ performance was measured by AUROC. The RFT model demonstrated excellent performances with accuracies up to 0.86 and AUROC up to 0.87. Feature selection in RF and SHAP was similar, and the choice of the best variable subset produced a high performance with an AUROC up to 0.89. We have developed a hybrid machine learning model with better predictive performance than traditional LR prediction models, as well as other machine learning models for cholangitis based on simple clinical data. The model can assist doctors in clinical diagnosis, adopt reasonable treatment plans, and improve the survival rate of patients.
Assessing the causal relationship between circulating immune cells and abdominal aortic aneurysm by bi-directional Mendelian randomization analysis
Authors: Ruan Weiqiang , Zhou Xiaoqin , Wang Ting , Liu Huizhen , Zhang Guiying , Sun Jiaoyan , Lin Ke
Published: June 2024

Although there is an association between abdominal aortic aneurysm (AAA) and circulating immune cell phenotypes, the exact causal relationship remains unclear. This study aimed to explore the causal relationships between immune cell phenotypes and AAA risk using a bidirectional two-sample Mendelian randomization approach. Data from genome-wide association studies pertaining to 731 immune cell traits and AAA were systematically analyzed. Using strict selection criteria, we identified 339 immune traits that are associated with at least 3 single nucleotide polymorphisms. A comprehensive MR analysis was conducted using several methods including Inverse Variance Weighted, Weighted Median Estimator, MR-Egger regression, Weighted Mode, and Simple Median methods. CD24 on switched memory cells (OR = 0.922, 95% CI 0.914–0.929, P = 2.62e−79) at the median fluorescence intensities level, and SSC-A on HLA-DR + natural killer cells (OR = 0.873, 95% CI 0.861–0.885, P = 8.96e−81) at the morphological parameter level, exhibited the strongest causal associations with AAA. In the reverse analysis, no significant causal effects of AAA on immune traits were found. The study elucidates the causal involvement of multiple circulating immune cell phenotypes in AAA development, signifying their potential as diagnostic markers or therapeutic targets. These identified immune traits may be crucial in modulating AAA-related inflammatory pathways.
Weakened continental lithosphere beneath the northern Red Sea inferred from elastic thickness
Authors: Jallouli Chokri , Al-Dini Waleed , Mogren Saad , Alzahrani Hassan
Published: June 2024

The northern Red Sea (NRS) is considered an extended continental region that has resulted in a rift system. Gravity and bathymetry data were used to estimate the Moho depth and the elastic thickness Te of the lithosphere beneath the NRS region to characterize its flexural rigidity and understand its mechanical behavior. Focusing on the Mabahiss Deep in NRS, we analyzed the lithosphere's flexural rigidity. The observed long-wavelength positive Bouguer anomaly is attributed to crustal thinning and lithospheric mantle uplift. The crustal thickness varies from 28 km in coastal areas to 24 km beneath the axial rift, supporting a regional compensation model over the Airy model. Forward modeling suggests that the optimal model explaining the regional Bouguer anomaly is a flexural model with Te equal to 7 km, indicating a weak and irregular continental crust. The primary factor contributing to this weakness is heating activity. Given the weakened state of the crust and the ongoing extension in the region, the NRS rift could evolve into a rupture, potentially leading to the formation of oceanic crust.