bluuebunny/crossref_metadata_2025_split huggingface dataset:
Accelerated amyloid fibril formation at the interface of liquid–liquid phase‐separated droplets by depletion interactions
Authors: Yamaguchi Keiichi , Mima Joji , Nakajima Kichitaro , Sakuta Hiroki , Yoshikawa Kenichi , Goto Yuji 
Published: January 2025

AbstractAmyloid fibril formation of α‐synuclein (αSN) is a hallmark of synucleinopathies. Although the previous studies have provided numerous insights into the molecular basis of αSN amyloid formation, it remains unclear how αSN self‐assembles into amyloid fibrils in vivo. Here, we show that αSN amyloid formation is accelerated in the presence of two macromolecular crowders, polyethylene glycol (PEG) (MW: ~10,000) and dextran (DEX) (MW: ~500,000), with a maximum at approximately 7% (w/v) PEG and 7% (w/v) DEX. Under these conditions, the two crowders induce a two‐phase separation of upper PEG and lower DEX phases with a small number of liquid droplets of DEX and PEG in PEG and DEX phases, respectively. Fluorescence microscope images revealed that the interfaces of DEX droplets in the upper PEG phase are the major sites of amyloid formation. We consider that the depletion interactions working in micro phase‐segregated state with DEX and PEG systems causes αSN condensation at the interface between solute PEG and DEX droplets, resulting in accelerated amyloid formation. Ultrasonication further accelerated the amyloid formation in both DEX and PEG phases, confirming the droplet‐dependent amyloid formation. Similar PEG/DEX‐dependent accelerated amyloid formation was observed for amyloid β peptide. In contrast, amyloid formation of β2‐microglobulin or hen egg white lysozyme with a native fold was suppressed in the PEG/DEX mixtures, suggesting that the depletion interactions work adversely depending on whether the protein is unfolded or folded.
Transcriptome‐Wide Association Study Identified Novel Blood Tissue Gene Biomarkers for Prostate Cancer Risk
Authors: Sun Yanfa , Zhu Jingjing , Zhong Hua , Zhang Zichen , Wang Fubo , Nakamura Akira , Liu Yanhui , Liu Jiawen , Yu Jie , Zeng Guanghua , Lin Xin , Zhou Dan , Wu Chong , Wang Liang , Deng Youping , Wu Lang 
Published: January 2025

ABSTRACTObjectiveA number of susceptibility genes in prostate tissue have been identified to be associated with prostate cancer (PCa) risk. However, the reported genes based on assessing prostate tissue could not fully explain PCa genetic susceptibility. It is believed that genes functioning in the immune system may fill in the gap of some missing heritability.MethodsTo study potential susceptibility genes acting in such pathways, we performed a transcriptome‐wide association study (TWAS) of 79,194 PCa cases and 61,112 control of European ancestry by using three sets of gene expression prediction models of blood tissue.ResultsA total of 470 genes were associated at false discovery rates‐corrected p‐value < 0.05, of which 51 were implicated as likely causal genes based on fine‐mapping analysis. Compared with previous literature, 133 novel genes were reported for the first time. Of the identified genes, five (CREB3L4, GSTP1, MAPK3, NKX3‐1, and PIK3C2B) were enriched in a PCa signaling pathway, and 128 genes were enriched in five PCa categories. Importantly, 13 genes (SCP2, LMNA, ZNF148, H2AFV, TACC1, FLII, SUPT4H1, CD300LF, MYO9B, COX6B1, CTSA, EP300, and TSPO) showed consistent effect directions for the measured levels in circulating immune cells between PCa cases and controls, and 14 genes (SLC39A1, ZBTB7B, TRIM59, NCEH1, N4BP2, TAGAP, TACC1, TRAF1, AIP, SECTM1, C18orf54, ZNF793, YIF1B, and TSPO) showed consistency for levels in blood exosomes between PCa patients and controls.ConclusionThe identified blood‐based candidate susceptibility genes provide further insights into the genetic basis of PCa risk.
Field measurement of spray drift from a spray application by UAV
Authors: Butler‐Ellis M Clare , Lane Andrew G. , O'Sullivan Christine M. , Wheeler Helen C. , Harwood Jeremy J. 
Published: January 2025

AbstractBACKGROUNDTo use unmanned aerial vehicles (UAVs) to deliver pesticides, new data are needed to allow regulators to conduct risk assessments. A field trial was conducted to obtain spray drift data relating to ground deposits and airborne spray resulting from a spray application delivered by a small UAV.RESULTSA 12 m width area was sprayed with four passes of the UAV and spray deposits were collected within the sprayed area and up to 50 m downwind. Airborne spray was collected at 5 and 10 m downwind. Ground deposits of spray drift were similar to other data produced by orchard airblast sprayers; airborne spray was generally lower than other data produced by boom sprayers.CONCLUSIONDrift data was obtained to allow regulators to conduct a risk assessment for a pesticide application delivered by the UAV configuration used in this study. The ability to control the operation and to record applied doses was inadequate and the distribution within the sprayed area was poor. © 2025 Society of Chemical Industry.
Growth of 6 Inch Diameter β‐Ga2O3 Crystal by the Vertical Bridgman Method
Authors: Igarashi Takuya , Ueda Yuki , Koshi Kimiyoshi , Sakaguchi Ryoichi , Watanabe Shinya , Yamakoshi Shigenobu , Kuramata Akito 
Published: January 2025

A 6 inch β‐gallium oxide (β‐Ga2O3) single crystal is grown in the ⟨010⟩ direction using the vertical Bridgman (VB) method under an oxygen partial pressure of 50%. Although cracks are observed along the cleavage planes, crossed polarizer microscopy confirms the absence of grain boundaries in the wafers. X‐ray rocking curve measurements demonstrate a consistent level of crystal quality, with an average full width at half maximum of 22.56 arcsec. Observation of the quenched solid–liquid interface reveals a slightly convex shape. The actual growth rate, calculated from the experimental data, suggests that crystal growth does not fully keep pace with the crucible descent process. The effect of the furnace temperature gradient is investigated by comparing a higher gradient (4–15 °C cm−1) with a lower gradient (0.5–5 °C cm−1). The crystal grown under the higher gradient exhibits no grain boundaries, whereas those grown under the lower gradient shows grain boundaries and significant cracking, making it unsuitable for wafer processing. These results demonstrate the feasibility of growing 6 inch β‐Ga2O3 single crystals using the VB method and suggest that further optimization of conditions, including control of the temperature gradient, are essential to achieve higher quality and greater stability.
Potential of Green Gold Nanoparticles Synthesized from Punica granatum Extract on Leishmaniasis and Breast Cancer Treatment
Authors: Kelleci Kubra 
Published: January 2025

AbstractIn the current study, the physicochemical properties and biological activities of gold nanoparticles (AuNP) synthesized in small sizes by Punica granatum using the green synthesis method and the chemical method were compared. UV–vis peak of chemically and biologically synthesized AuNPs was confirmed at 540 nm and 535 nm, respectively. By FT‐IR analysis, it was revealed that there were active biomolecules in Punica granatum extract for the synthesis of green AuNPs. According to XRD results, broad spectra were obtained. The crystalline nature of Green AuNP was demonstrated. Using SEM and DLS, it was observed that green AuNP had dimensions between 4–6 nm and chemical AuNP had dimensions between 6–12 nm. Punica granatum‐based AuNPs were more effective in the MDA‐MB‐231 breast cancer cell line than AuNPs by chemical method. It has also been revealed that green AuNPs are much more effective than chemical AuNPs against L. infantum parasites. As a result, Punica granatum‐based green AuNPs have been proven to be functionally more efficient and effective than chemically prepared AuNPs. Our study will encourage researchers to increase the synthesis of green NPs for medical use.
Therapeutic Insights of Indole Scaffold‐Based Compounds as Protein Kinase Inhibitors
Authors: Dawood Dina H. 
Published: January 2025

AbstractCancer is deemed to be one of the most severe diseases, which is accountable for the elevated mortality rate after cardiovascular diseases. Despite the huge numbers of drugs that were approved by the USFDA to combat the prevalence of cancer, the resistance of the diverse cancer types to the current medications as well as their high toxicity becomes an obstacle in cancer therapy. Thus, the developing of new medications with improved selectivity and efficiency to cure various types of cancer disease is still an imperative goal. Kinases are phosphorylating enzymes that catalyze the transfer of phosphate from ATP to tyrosine, serine and threonine residues of proteins, which leads to the activation of varied signaling pathways that regulate various cellular functions such as differentiation, proliferation, migration and angiogenesis. Abnormal phosphorylation leads to various diseases such as cancer, overexpression of kinases was frequently observed in different cancerous tissues. Thus, the suppression of the kinase activity has stood out as a strategic pathway for cancer therapy. Otherwise, indole core has displayed as a privileged scaffold with promising anticancer properties and multi‐kinase suppression effect. This review presents various indole‐based anticancer agents as kinase inhibitors in the recent decade. In addition, the various interactions of indole derivatives within the active pocket of different kinases have been highlighted. This review article comprises research reports from 2014 until the present.
From Quantum Curves to Topological String Partition Functions II
Authors: Coman Ioana , Longhi Pietro , Teschner Jörg 
Published: January 2025

Abstract
We propose a geometric characterisation of the topological string partition functions associated with the local Calabi–Yau (CY) manifolds used in the geometric engineering of

$$d=4$$

d
=
4

,

$${\mathcal {N}}=2$$

N
=
2

supersymmetric field theories of class

$${\mathcal {S}}$$

S

. A quantisation of these CY manifolds defines differential operators called quantum curves. The partition functions are extracted from the isomonodromic tau-functions associated with the quantum curves by expansions of generalised theta series type. It turns out that the partition functions are in one-to-one correspondence with preferred coordinates on the moduli spaces of quantum curves defined using the Exact WKB method. The coordinates defined in this way jump across certain loci in the moduli space. The changes of normalization of the tau-functions associated with these jumps define a natural line bundle playing a key role in the geometric characterisation of the topological string partition functions proposed here.
Optimal stopping of BSDEs with constrained jumps and related double obstacle PDEs
Authors: Perninge Magnus 
Published: January 2025

Abstract
We consider partial differential equations (PDEs) characterized by an upper barrier that depends on the solution itself and a fixed lower barrier, while accommodating a non-local driver. First, we show a Feynman–Kac representation for the PDE when the driver is local. Specifically, we relate the non-linear Snell envelope, arising from an optimal stopping problem—where the underlying process is the first component in the solution to a stopped backward stochastic differential equation (BSDE) with jumps and a constraint on the jumps process—to a viscosity solution for the PDE. Leveraging this Feynman–Kac representation, we subsequently prove existence and uniqueness of viscosity solutions in the non-local setting by employing a contraction argument. This approach also introduces a novel form of non-linear Snell envelope and expands the probabilistic representation theory for PDEs.
Prediction of electrohydrodynamic printing behavior using machine learning approaches
Authors: Lu Yizhou , Treadway James , Ghimire Prashant , Han Yiwei , Choudhury Samrat 
Published: January 2025

Abstract
Electrohydrodynamic (EHD) printing has been used in various applications (e.g., sensors, batteries, photonic crystals). Currently, research on studying the relationships between EHD jetting behaviors, material properties, and processing conditions is still challenging due to a large number of parameters, cost, time, and the complex nature of experiments. In this research, we investigated EHD printing behavior using a machine learning (ML)-guided approach to overcome limitations in the experiments. Specifically, we investigated two jetting modes and the size of printed material with a broader range of material properties and processing parameters. We used samples from both literature and our own experiment results with different type of materials. Different ML models have been developed and applied to the data. Our results have shown that ML can navigate a vast parameter search space to predict printing behavior with an accuracy of higher than 95% during EHD printing. Moreover, the results showed that ML models can be used to predict the printing behavior and feather size for new materials. The ML models can guide the investigation of EHD printing and helped us understand the printing behavior in a systematic manner with reduced time, cost, and required experiments.
Curvature and sharp growth rates of log-quasimodes on compact manifolds
Authors: Huang Xiaoqi , Sogge Christopher D. 
Published: January 2025

Abstract
We obtain new optimal estimates for the

$L^{2}(M)\to L^{q}(M)$

L
2

(
M
)
→

L
q

(
M
)

,

$q\in (2,q_{c}]$

q
∈
(
2
,

q
c

]

,

$q_{c}=2(n+1)/(n-1)$

q
c

=
2
(
n
+
1
)
/
(
n
−
1
)

, operator norms of spectral projection operators associated with spectral windows

$[\lambda ,\lambda +\delta (\lambda )]$

[
λ
,
λ
+
δ
(
λ
)
]

, with

$\delta (\lambda )=O((\log \lambda )^{-1})$

δ
(
λ
)
=
O
(

(
log
λ
)

−
1

)

on compact Riemannian manifolds

$(M,g)$

(
M
,
g
)

of dimension

$n\ge 2$

n
≥
2

all of whose sectional curvatures are nonpositive or negative. We show that these two different types of estimates are saturated on flat manifolds or manifolds all of whose sectional curvatures are negative. This allows us to classify compact space forms in terms of the size of

$L^{q}$

L
q

-norms of quasimodes for each Lebesgue exponent

$q\in (2,q_{c}]$

q
∈
(
2
,

q
c

]

, even though it is impossible to distinguish between ones of negative or zero curvature sectional curvature for any

$q>q_{c}$

q
>

q
c

.
Generative artificial intelligence enables the generation of bone scintigraphy images and improves generalization of deep learning models in data-constrained environments
Authors: Haberl David , Ning Jing , Kluge Kilian , Kumpf Katarina , Yu Josef , Jiang Zewen , Constantino Claudia , Monaci Alice , Starace Maria , Haug Alexander R. , Calabretta Raffaella , Camoni Luca , Bertagna Francesco , Mascherbauer Katharina , Hofer Felix , Albano Domenico , Sciagra Roberto , Oliveira Francisco , Costa Durval , Nitsche Christian , Hacker Marcus , Spielvogel Clemens P. 
Published: January 2025

Abstract

Purpose
Advancements of deep learning in medical imaging are often constrained by the limited availability of large, annotated datasets, resulting in underperforming models when deployed under real-world conditions. This study investigated a generative artificial intelligence (AI) approach to create synthetic medical images taking the example of bone scintigraphy scans, to increase the data diversity of small-scale datasets for more effective model training and improved generalization.

Methods
We trained a generative model on 99mTc-bone scintigraphy scans from 9,170 patients in one center to generate high-quality and fully anonymized annotated scans of patients representing two distinct disease patterns: abnormal uptake indicative of (i) bone metastases and (ii) cardiac uptake indicative of cardiac amyloidosis. A blinded reader study was performed to assess the clinical validity and quality of the generated data. We investigated the added value of the generated data by augmenting an independent small single-center dataset with synthetic data and by training a deep learning model to detect abnormal uptake in a downstream classification task. We tested this model on 7,472 scans from 6,448 patients across four external sites in a cross-tracer and cross-scanner setting and associated the resulting model predictions with clinical outcomes.

Results
The clinical value and high quality of the synthetic imaging data were confirmed by four readers, who were unable to distinguish synthetic scans from real scans (average accuracy: 0.48% [95% CI 0.46–0.51]), disagreeing in 239 (60%) of 400 cases (Fleiss’ kappa: 0.18). Adding synthetic data to the training set improved model performance by a mean (± SD) of 33(± 10)% AUC (p < 0.0001) for detecting abnormal uptake indicative of bone metastases and by 5(± 4)% AUC (p < 0.0001) for detecting uptake indicative of cardiac amyloidosis across both internal and external testing cohorts, compared to models without synthetic training data. Patients with predicted abnormal uptake had adverse clinical outcomes (log-rank: p < 0.0001).

Conclusions
Generative AI enables the targeted generation of bone scintigraphy images representing different clinical conditions. Our findings point to the potential of synthetic data to overcome challenges in data sharing and in developing reliable and prognostic deep learning models in data-limited environments.

Graphical abstract
The spinel to garnet phase transition in the systems MgO-Al2O3-SiO2 and CaO-MgO-Al2O3-SiO2: new experiments to resolve long-standing discrepancies
Authors: Farmer Nicholas , O’Neill Hugh St. C. , Green Eleanor C. R. 
Published: January 2025

Abstract
The pressure and temperature conditions of the transition from spinel to garnet as the stable aluminous phase in peridotite lithologies of the upper mantle is integral to elucidating the tectonic significance of the ‘garnet signature’ in basalts. It provides an essential constraint on models of mantle partial melting and oceanic crust formation. Existing experimental results on the univariant phase transition in the simple systems MgO-Al2O3-SiO2 (MAS) and CaO-MgO-Al2O3-SiO2 (CMAS) are mutually inconsistent. To resolve this, we have re-determined the P-T coordinates of the univariant transition in both synthetic systems by running experiments containing both systems simultaneously in the piston-cylinder apparatus, along with the MgO-ZnO pressure sensor. These experiments show a ~ 0.4 GPa difference in the pressure of the spinel/garnet phase transition between the two chemical systems at 1400 ºC, double that inferred from a compilation of existing experimental data. Absolute pressure in these experiments can be verified using the MgO-ZnO sensor. The results imply that the thermodynamic data used in recent mineral equations of state based on the Holland-Powell thermodynamic dataset are substantially correct.
Nonlocal effects on curved double-walled carbon nanotubes based on nonlocal theory
Authors: Tepe Ayşegül 
Published: January 2025

Abstract
Curved double-walled carbon nanotubes (CDWCNTs) are crucial components in nanoelectronics, mechanical sensors, and composite materials due to their unique geometry and structural properties. Electron microscopy images have revealed that carbon nanotubes are rarely perfectly straight, often exhibiting curvature or waviness along their length due to inherent geometrical imperfections. The accurate mechanical modeling of these structures is essential, particularly to capture size-dependent effects that classical elasticity theories fail to account for. In this study, a novel analytical framework was introduced for combining the initial value method with the approximate transfer matrix approach to analyze the mechanical behavior of CDWCNTs under anti-plane loading within the framework of nonlocal elasticity theory. The proposed methodology provides an effective and computationally efficient alternative to traditional analytical approaches. By analyzing displacements, rotations, bending moments, and shear forces, substantial deviations were revealed between classical and nonlocal elasticity solutions, particularly as the dimensionless nonlocal parameter

$$R/\gamma $$

R
/
γ

decreased. The results show that nonlocal effects become dominant at smaller size parameters, especially in displacements, rotations, and bending moments, while shear forces remain unaffected. These findings emphasize the critical role of nonlocal effects in accurately predicting nanoscale mechanical responses and offer valuable insights for modeling advanced nanostructures in emerging technologies, such as microelectromechanical systems and nanotechnology. Convergence studies have confirmed the accuracy and stability of the proposed approach, thereby establishing this as a robust tool for modeling nanoscale structures.
Probabilistic tephra fallout hazard maps for Sangay volcano, Ecuador
Authors: Tadini Alessandro , Pardini Federica , Bevilacqua Andrea , Bernard Benjamin , Samaniego Pablo , Vitturi Mattia de’ Michieli , Aravena Alvaro , Hidalgo Silvana , Roche Olivier , Azzaoui Nourddine , Neri Augusto , Aguilar Jorge 
Published: January 2025

Abstract
Sangay volcano (Ecuador) shows a quasi-continuous activity at least since the seventeenth century and has produced several eruptions which affected towns and cities at considerable distance (up to > 170 km). For this reason, despite its remote location, recent efforts were aimed at reviewing its volcanic history, quantifying the occurrence probability of four eruptive scenarios of different magnitude (Strong Ash Venting, Violent Strombolian, sub-Plinian, and Plinian) and the associated uncertainty, and, for each eruptive scenario, estimating the probability distribution of key eruptive source parameters (fallout volume, average plume height, and eruption duration). In this study, we utilize such information to produce probabilistic hazard maps and curves. To this aim, we use coupled plume and dispersal models (PLUME-MOM-TSM and HYSPLIT, respectively) with the application of a novel workflow for running an ensemble of thousands of simulations following a stochastic sampling of input parameters. We produced probabilistic hazard maps for each scenario by considering four ground load thresholds (i.e., 0.1, 1, 10, and 100 kg/m2) and two types of model initialization strategies, based on the elicited total deposit volume and on the elicited plume height, respectively, which produced non-negligible differences. In addition, we produced hazard curves for nine sites of interest from a risk perspective, corresponding to towns/cities potentially affected by tephra accumulation. Finally, we also derived combined maps by merging maps of single scenarios with their probability of occurrence as obtained from expert elicitation. Results indicate that in case of a future eruption, even for a moderate-scale one (Violent Strombolian), probability of tephra accumulation larger than 1 kg/m2 is relatively high (from 21 to 24% considering different model initializations) in the town of Guamote, i.e., the most severely affected site among those tested (43 km W of Sangay). For larger-scale events (i.e., sub-Plinian), the impact of tephra accumulation results to be significant even for the city of Guayaquil (176 km W of Sangay), with probability of tephra accumulation larger than 1 kg/m2 from 3 to 22% considering different model initializations. For maps combining single maps of historically observed scenarios, the probability (% - [5th-Mean-95th]) of having ≥ 10 kg/m2 for Guamote is [4-13-25] as maximum values.