bluuebunny/crossref_metadata_2025_split huggingface dataset:
Characterization of a primary cellular airway model for inhalative drug delivery in comparison with the established permanent cell lines CaLu3 and RPMI 2650
Authors: Martin Janik , Rittersberger Rebecca , Treitler Simon , Kopp Patrick , Ibraimi Anit , Koslowski Gabriel , Sickinger Max , Dabbars Annabelle , Schindowski Katharina 
Published: November 2024

Abstract
Purpose
For optimization of respiratory drug delivery, the selection of suitable in vitro cell models plays an important role in predicting the efficacy and safety of (bio)pharmaceutics and pharmaceutical formulations. Therefore, an in-depth comparison of different primary and permanent in vitro cellular airway models was performed with a focus on selecting a suitable model for inhalative antibodies.

Methods
Primary cells isolated from the porcine trachea were compared with the established human cell lines CaLu3 and RPMI 2650. The in vitro models were characterized for different epithelial markers by real-time quantitative polymerase chain reaction, which provides insight into the cellular composition of each model. For a few selected markers, the results from RT-qPCR were confirmed via immunofluorescence. Barrier integrity was assessed by transepithelial electrical resistance measurements and FITC-dextran permeability.

Results
Primary cell models retain key features of the respiratory epithelium, e.g., the formation of a tight epithelial barrier, mucin production, and the presence of club/basal cells. Furthermore, the expression of Fc receptors in the primary cell models closely resembles that in respiratory mucosal tissue, an essential parameter to consider when developing therapeutic antibodies for inhalation.

Conclusion
The study underlines the importance of selecting wisely appropriate in vitro models. Despite the greater effort and variability in cultivating primary airway cells, they are far superior to permanent cells and a suitable model for drug development.
Barriers and facilitators to implementing adaptive trial designs in paediatric critical care: an international mixed-methods study
Authors: Gilholm Patricia , Wu Ken , Le Marsney Renate , Gibbons Kristen 
Published: November 2024

Abstract
Aims
This study aimed to identify the barriers and facilitators to implementing adaptive trial designs in paediatric intensive care unit (PICU) trials.

Methods
A mixed-methods approach was used, combining an electronic survey and semi-structured interviews. The survey targeted clinicians and researchers involved in PICU trials, collecting information on their knowledge, and experience with adaptive trial designs. Semi-structured interviews were conducted with experienced international PICU trialists to explore themes related to adaptive trial design development and implementation.

Results
Eighty-six survey responses were collected from 21 countries, with 62 responses from 20 countries eligible for analysis. Of these, 45% (n = 28) of respondents had experience with adaptive trials, particularly in platform trials (n = 9, 32%) and adaptive randomisation (n = 8, 29%). Barriers to implementation included statistical complexities, infrastructure requirements, and a lack of expertise. Facilitators included increasing understanding of adaptive methodologies and access to statistical expertise. Ten interviews were conducted. Interview themes highlighted optimism about adaptive designs, a lack of formal training, the need for collaboration, the role of high-profile trials, and the potential risks involved.

Conclusions
Adaptive trial designs in PICU trials hold promise but are underutilised due to substantial barriers, particularly in statistical and infrastructural areas. Addressing these challenges, promoting formal training, enhancing collaboration, and raising awareness of adaptive trial methodologies are critical to increasing their adoption in paediatric critical care.
Technologies and applications in wireless biosensors for real-time health monitoring
Authors: Xu Zitong , Hao Yuetong , Luo Amy , Jiang Yuanwen 
Published: November 2024

AbstractWireless biosensing has emerged as a critical technology due to its ability to provide real-time, continuous monitoring of physiological parameters without the constraints of wired connections. This review starts from the fundamental mechanisms of physical and chemical sensing in wireless biosensors, to the integration of advanced wireless technologies for energy harvesting and data communication, including Radio Frequency, Bluetooth, and other forms. Additionally, it covers diverse applications in wearable and implantable biosensors, such as cardiac monitoring, prosthetic enhancements, electronic skin and contact lenses. Attention is given to the emerging fields of osseosurface electronics and gastrointestinal capsule sensors, which represent significant advancements in non-invasive and minimally invasive health monitoring. The synergistic integration of these technologies paves the way for innovative diagnostic and therapeutic tools, promising improved patient outcomes and convenient healthcare solutions. This comprehensive overview aims to provide insights into the current state and future prospects of wireless biosensing technologies, underscoring their potential to be realized in various kinds of biosensors.
Graphical Abstract
A deep operator network for Bayesian parameter identification of self-oscillators
Authors: Sugandi Tobias , Dharmaputra Bayu , Noiray Nicolas 
Published: November 2024

Abstract
Many physical systems exhibit limit-cycle oscillations that can typically be modeled as stochastically driven self-oscillators. In this work, we focus on a self-oscillator model where the nonlinearity is on the damping term. In various applications, it is crucial to determine the nonlinear damping term and the noise intensity of the driving force. This article presents a novel approach that employs a deep operator network (DeepONet) for parameter identification of self-oscillators. We build our work upon a system identification methodology based on the adjoint Fokker–Planck formulation, which is robust to the finite sampling interval effects. We employ DeepONet as a surrogate model for the operator that maps the first Kramers–Moyal (KM) coefficient to the first and second finite-time KM coefficients. The proposed approach can directly predict the finite-time KM coefficients, eliminating the intermediate computation of the solution field of the adjoint Fokker–Planck equation. Additionally, the differentiability of the neural network readily facilitates the use of gradient-based optimizers, further accelerating the identification process. The numerical experiments demonstrate that the proposed methodology can recover desired parameters with a significant reduction in time while maintaining an accuracy comparable to that of the classical finite-difference approach. The low computational time of the forward path enables Bayesian inference of the parameters. Metropolis-adjusted Langevin algorithm is employed to obtain the posterior distribution of the parameters. The proposed method is validated against numerical simulations and experimental data obtained from a linearly unstable turbulent combustor.
When filth became dangerous: the miasmatic and contagionistic origins of nineteenth-century cleanliness practices among Swedish provincial doctors
Authors: Drakman Annelie 
Published: November 2024

Abstract
This investigation sheds light on the social history of pathogenic dirt and its significance for shaping medical practices during the nineteenth century. It consists of an analysis focusing on Swedish medicine, using 8800 yearly reports written 1820–1900 by Swedish provincial doctors for the National Board of Health in Stockholm. The main argument is that the provincial doctors’ perceptions of the relationship between dirt and health during this century can be better understood by focusing on similarities in the handling of different kinds of pathological dirt over the course of many decades, rather than seeing interest in cleanliness as something mostly unprecedented. A novel cleanliness regime became dominant during the latter third of the century, meant to counter a new hybrid between everyday dirt – bodily emanations from healthy bodies – and matter believed to have caused miasmatic and contagionistic disease. New ideas about filth and its impact on health played a crucial role in the development of public health and sanitation movements, and were a precondition for everyday dirt becoming a central medical problem around the turn of the twentieth century, but as is shown, they built on old precedents. Thus, the miasmatic and contagionistic approach to disease shaped conceptions of hygiene and cleanliness.
ADDITIVE AND SUBTRACTIVE BASES OF
$\mathbb {Z}_m$
IN AVERAGE
Authors: LIANG GUANGPING , ZHANG YU , ZUO HAODE 
Published: November 2024

Abstract
Given a positive integer m, let

$\mathbb {Z}_m$

be the set of residue classes mod m. For

$A\subseteq \mathbb {Z}_m$

and

$n\in \mathbb {Z}_m$

, let

$\sigma _A(n)$

be the number of solutions to the equation

$n=x+y$

with

$x,y\in A$

. Let

$\mathcal {H}_m$

be the set of subsets

$A\subseteq \mathbb {Z}_m$

such that

$\sigma _A(n)\geq 1$

for all

$n\in \mathbb {Z}_m$

. Let

$$ \begin{align*} \ell_m=\min\limits_{A\in \mathcal{H}_m}\bigg\lbrace m^{-1}\sum_{n\in \mathbb{Z}_m}\sigma_A(n)\bigg\rbrace. \end{align*} $$

Ding and Zhao [‘A new upper bound on Ruzsa’s numbers on the Erdős–Turán conjecture’, Int. J. Number Theory20 (2024), 1515–1523] showed that

$\limsup _{m\rightarrow \infty }\ell _m\le 192$

. We prove

$$ \begin{align*} \limsup\limits_{m\rightarrow\infty}\ell_m\leq 144 \end{align*} $$

and investigate parallel results on subtractive bases of

$ \mathbb {Z}_m$

.
The planar 3-colorable subgroup ε of Thompson’s group F and its even part
Authors: Aiello Valeriano , Nagnibeda Tatiana 
Published: November 2024

AbstractWe study the planar 3-colorablesubgroup $\mathcal{E}$ of Thompson’s group F and its even part ${\mathcal{E}_{\rm EVEN}}$. The latter is obtained by cutting $\mathcal{E}$ with a finite index subgroup of F isomorphic to F, namely the rectangular subgroup $K_{(2,2)}$. We show that the even part ${\mathcal{E}_{\rm EVEN}}$ of the planar 3-colorable subgroup admits a description in terms of stabilisers of suitable subsets of dyadic rationals. As a consequence ${\mathcal{E}_{\rm EVEN}}$ is closed in the sense of Golan and Sapir. We then study three quasi-regular representations associated with ${\mathcal{E}_{\rm EVEN}}$: two are shown to be irreducible and one to be reducible.
RIGIDITY FOR VON NEUMANN ALGEBRAS OF GRAPH PRODUCT GROUPS II. SUPERRIGIDITY RESULTS
Authors: Chifan Ionuţ , Davis Michael , Drimbe Daniel 
Published: November 2024

AbstractIn [CDD22], we investigated the structure of
$\ast $
-isomorphisms between von Neumann algebras
$L(\Gamma )$
associated with graph product groups
$\Gamma $
of flower-shaped graphs and property (T) wreath-like product vertex groups, as in [CIOS21]. In this follow-up, we continue the structural study of these algebras by establishing that these graph product groups
$\Gamma $
are entirely recognizable from the category of all von Neumann algebras arising from an arbitrary nontrivial graph product group with infinite vertex groups. A sharper
$C^*$
-algebraic version of this statement is also obtained. In the process of proving these results, we also extend the main
$W^*$
-superrigidity result from [CIOS21] to direct products of property (T) wreath-like product groups.
Sentinel‐1 Snow Depth Assimilation to Improve River Discharge Estimates in the Western European Alps
Authors: Brangers I. , Lievens H. , Getirana A. , De Lannoy G. J. M. 
Published: November 2024

AbstractSeasonal snow is an important water source and contributor to river discharge in mountainous regions. Therefore the amount of snow and its distribution are necessary inputs for hydrological modeling. Recent research has shown the potential of the Sentinel‐1 radar satellite to map snow depth (SD) at sub‐kilometer resolution in mountainous regions. In this study we assimilate these new SD retrievals into the Noah‐Multiparameterization land surface model using an ensemble Kalman filter for the western European Alps. The land surface model was coupled to the Hydrological Modeling and Analysis Platform (HyMAP), a global flow routing scheme that provides simulations of routed river discharge. The performance with different precipitation forcing inputs, namely MERRA‐2 (with and without gauge based correction) and ERA5, was compared based on in situ precipitation and SD stations, with ERA5 leading to the best SD performance. The Sentinel‐1 based data assimilation (DA) results show small but systematic improvements for SD estimates, with the mean absolute error reducing from 36.4 cm for the open loop (OL) to 35.6 cm for the DA across all stations and timesteps, improving 318 out of 516 in situ sites. The DA updates in SD also result in enhanced snow water equivalent and discharge simulations. The median temporal correlation between discharge simulations and measurements increases from 0.73 to 0.78 for the DA. This study demonstrates the utility of the Sentinel‐1 SD retrievals to improve not only the representation of snow in mountain ranges, but also the snow melt contribution to river discharge, and hydrological modeling in general.
Comment on “Improving Bayesian Model Averaging for Ensemble Flood Modeling Using Multiple Markov Chains Monte Carlo Sampling”
Authors: Vrugt Jasper A. 
Published: November 2024

AbstractHuang and Merwade (2023), https://doi.org/10.1029/2023wr034947, hereafter conveniently referred to as HM23, wrongly claim improvement of their method for postprocessing multi‐model water stage predictions using Bayesian Model Averaging (BMA). Their results show all signs of a flawed implementation of the Metropolis algorithm. In this comment I will point out the many mistakes and shortcomings of the BMA methodology of HM23. Their method is deficient, inefficient and ineffective and wrongly quantifies BMA model parameter and predictive uncertainty. Furthermore, HM23 misrepresent BMA literature, articulate a poor understanding of Markov chain Monte Carlo methods and misuse the autocorrelation function for monitoring convergence of the sampled Markov chains. A proper implementation of the random walk Metropolis algorithm would have led HM23 to substantially different results and findings about their ensemble of water stage predictions. The MODELAVG toolbox of Vrugt (2018) https://www.researchgate.net/publication/299458373_MODELAVG_A_MATLAB_Toolbox_for_Postprocessing_of_Model_Ensembles satisfies all requirements of HM23 and provides robust estimates of BMA model parameter and prediction uncertainty for symmetric, skewed and truncated conditional forecast distributions of the ensemble members.
The Double Peak Superposition on the Equatorial Ionization Anomaly Crests During the 23 April 2023 Storm
Authors: Yang Yanyan , Xiong Chao , Zhang Shun‐Rong , Yan Rui , Huang He , Zeren Zhima , Pu Weixing , Xu Song , Huang Jianping , Lu Hengxin , Xu Yue , Shen Xuhui 
Published: November 2024

AbstractThe typical equatorial ionization anomaly (EIA) exhibits two crests around the magnetic equator. Here we reported evidence for a double‐peak superposition at the EIA crest of each hemisphere, forming a four‐peak structure, with the additional peaks located ∼10° poleward of normal crests, as observed by CSES at 500 km altitudes on dayside, during the 23 April 2023 geomagnetic storm. Such a unique structure occurred when the eastward prompt penetration electric field (PPEF) was developed. Interestingly, distinctive large‐scale traveling ionospheric disturbances derived from GNSS‐TEC data propagated equatorward but not coincidently interacted with the EIA poleward peaks. The short‐duration intense PPEF may be the most plausible mechanism, which could cause the “fountain” plasma highly elevated into the topside which gradually fell into CSES altitudes on poleward sides of regular EIA crests, causing the superposition of crest in addition to nominal crest generated by the regular wind dynamo.
Dynamic Emergence of Plate Motions and Great Megathrust Earthquakes Across Length and Time Scales
Authors: Fang Jiaqi , Gurnis Michael , Lapusta Nadia 
Published: November 2024

AbstractThe slow motion of tectonic plates over thousands of kilometers is intermittently interrupted by great earthquakes with sudden slips localized near convergent plate boundaries. We developed a subduction model that self‐consistently integrates buoyancy forces, diffusion and dislocation creep, and inter‐plate friction. From the nonlinear dynamics emerge long‐term plate motions that achieve velocities of cm/year, effective viscosities of Pas below plates, and sudden slips up to m repeating every several hundred years. Along‐strike resistance arising from long‐wavelength variation of coseismic slip is naturally incorporated with a rupture length scale, . Computations with km generate events with . When decreases, there is a commensurate decrease in the effective moment of rupture events. Predicted long‐term plate velocities, mantle viscosities, cycles of stress loading and release, and rupture event size and magnitude all show good agreement with observations.
Enhanced Net Community Production With Sea Ice Loss in the Western Arctic Ocean Uncovered by Machine‐Learning‐Based Mapping
Authors: Zhou Tianyu , Li Yun , Ouyang Zhangxian , Cai Wei‐Jun , Ji Rubao 
Published: November 2024

AbstractIn the Arctic Ocean (AO), net community production () has displayed spatially heterogeneous responses to sea ice reduction and associated environmental changes. Using a random forest machine learning model trained with >42,000 in situ measurements and concurrent, collocated environmental predictors, we reconstructed 19 years of 8‐day, 6‐km maps. During 2015–2021, the integrated between late‐May and early‐September () over the western AO was per year, with interannual variations positively tracking open water area. While the relationship between and open water area was quasi‐linear at high latitudes, strong nonlinearity was detected on the inflow shelf. The nonlinearity highlights that the increase resulted from area gain could be compounded by sea‐ice loss induced ecosystem adjustments. Additional retrospective analysis for 2003–2014 suggests a potential long‐term increase of export production and efficiency in the western AO with sea ice loss.
Indications of Ongoing Noise‐Tipping of a Bifurcating River System
Authors: Blom Astrid , Ylla Arbós Clàudia , Chowdhury M. Kifayath , Doelman Arjen , Rietkerk Max , Schielen Ralph M. J. 
Published: November 2024

AbstractTipping occurs when a critical point is reached, beyond which a perturbation leads to persistent system change. Here, we present observational indications demonstrating presently ongoing noise‐tipping of a real‐world system. Noise in a river system is associated with the changing flow rate. In particular, we consider the upper Rhine River delta, where flow and sediment fluxes are partitioned over the two downstream branches (bifurcates) of an important river bifurcation. Field observations show that a sequence of peak flows in the 1990s resulted in sudden sediment deposition in one bifurcate, triggering a persistent and ongoing change in the flow partitioning. This has caused the system to move toward an alternative equilibrium state or attractor. An idealized model confirms that a river bifurcation system under such conditions is prone to tipping, and provides insight on the onset of tipping.
A Gaussian Variogram‐Based Model of Total Electron Content in the Regional Ionosphere of China
Authors: Liu Ang , Li Zishen , Wang Ningbo , Li Ang , Zhang Zhouyu , Zhang Yunlong 
Published: November 2024

AbstractThis study utilizes ionospheric total electron contents (TECs) data from China and its surrounding areas to compute the regional ionospheric semi‐variance using the Gaussian variogram. The regional ionospheric model is then constructed by introducing an additional stochastic term, named adjusted Spherical Harmonics Adding KrigING method (SHAKING), in which the stochastic Vertical Total Electron Content estimated using Kriging interpolation based on Ionospheric Variogram Model Parameters (IVMP) predict model. In the IVMP prediction model, two notable periodic patterns, that is, diurnal and annual signals with periods of 365.25/i days and 24/j hours, are recognized as Fourier series decompositions. These patterns capture the regular daily and yearly periodic variations in variogram parameters, and the IVMP prediction model is established using harmonic estimation methods. IVMP‐SHAKING is employed to generate the regional ionospheric map in China using multi‐GNSS data from 27 reference stations during days of the year 150–250 in 2022, with 14 rover stations used for evaluation. Results indicate that the proposed model exhibits a standard deviation of 4.85 TECu compared to the difference of slant TEC extracted from rover stations. Compared to existing models, including BDS‐3 broadcast ionospheric model (BDGIM), GPS broadcast model (Klobuchar), Galileo broadcast model (NeQuickG) and post‐processing Global Ionospheric Map released by IGS (IGSG), the accuracy of IVMP‐SHAKING improves by 6%–52%. Additionally, the Standard Point Positioning performance with different ionospheric corrections is analyzed on test stations. Results demonstrate that the horizontal and vertical positioning accuracy of the IVMP‐SHAKING model improves by 31%–55% and 16%–33%, respectively, compared to other three solutions.
A longitudinal study of hippocampal subfield volumes and hippocampal glutamate levels in antipsychotic-naïve first episode psychosis patients
Authors: Nelson Eric A. , Kraguljac Nina V. , Bashir Adil , Cofield Stacey S. , Maximo Jose O. , Armstrong William , Lahti Adrienne C. 
Published: November 2024

Abstract
Background
Previous studies have implicated hippocampal abnormalities in the neuropathology of psychosis spectrum disorders. Reduced hippocampal volume has been reported across all illness stages, and this atrophy has been hypothesized to be the result of glutamatergic excess. To test this hypothesis, we measured hippocampal subfield volumes and hippocampal glutamate levels in antipsychotic naïve first episode psychosis patients (FEP) and the progression of volume decline and changes in glutamate levels over a 16-week antipsychotic drug (APD) trial. We aimed to determine if subfield volumes at baseline were associated with glutamate levels, and if baseline glutamate levels were predictive of change in subfield volumes over time.

Methods
We enrolled ninety-three medication-naïve FEP participants and 80 matched healthy controls (HC). T1 and T2 weighted images and magnetic resonance spectroscopy (MRS) data from a voxel prescribed in the left hippocampus were collected from participants at baseline and after 6 and 16 weeks of APD treatment. Hippocampal subfield volumes were assessed using FreeSurfer 7.1.1., while glutamate levels were quantified using jMRUI version 6.0. Data were analyzed using linear mixed models.

Results
We found regional subfield volume deficits in the CA1, and presubiculum in FEP at baseline, that further expanded to include the molecular and granule cell layer of the dentate gyrus (GC/ML/DG) and CA4 by week 16. Baseline hippocampal glutamate levels in FEP were not significantly different than those of HC, and there was no effect of treatment on glutamate. Glutamate levels were not related to initial subfield volumes or volume changes over 16 weeks.

Conclusion
We report a progressive loss of hippocampal subfield volumes over a period of 16 weeks after initiation of treatment, suggestive of early progression in neuropathology. Our results do not suggest a role for glutamate as a driving factor. This study underscores the need to further research the mechanism(s) underlying this phenomenon as it has implications for early intervention to preserve cognitive decline in FEP participants.